Search results for ""Manning Publications""

DESCRIPTION OAuth 2 is like the web version of a valet key. Instead of unsafe password-sharing, OAuth offers a much more secure delegation protocol. OAuth is used everywhere, from large providers like Facebook and Google, to small APIs at startups, and even cloud services, it’s the worldwide standard. OAuth 2 is the must-know security protocol on the web today. OAuth 2 in Action teaches practical use and deployment of this protocol from the perspective of a client, authorization server, and resource server. It begins with an overview of OAuth and a look at its components and interactions. Using hands-on examples, it shows how to build a first OAuth client, followed by an authorization server, and then a protected resource. The second part of the book dives into crucial implementation vulnerability, and more advanced topics. By the end of this book, anyone will be able to build and deploy applications that use OAuth on both the client and server sides. KEY FEATURES • Hands-on examples • Connect with major online services like Google, Facebook, Twitter • Takes the reader from beginner to advanced OAuth 2 topics. AUDIENCE Readers need basic programming skills and knowledge of HTTP and JSON. ABOUT THE TECHNOLOGY This HTTP-based security protocol allows the users of a service to enable applications to use that service on their behalf without handing over full control. Web and mobile apps can securely access information from other servers for users, enabling apps to give these users functionality and services from other sites.

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DESCRIPTION There's priceless insight trapped in the flood of data users leave behind as they interact with web pages and applications. Those insights can be unlocked by using intelligent algorithms like the ones that have earned Facebook, Google, Twitter, and Microsoft a place among the giants of web data pattern extraction. Improved search, data classification, and other smart pattern matching techniques can give an enormous advantage to understanding and interacting with users. Algorithms of the Intelligent Web, Second Edition has been totally revised and teaches the most important approaches to algorithmic web data analysis, enabling readers to create machine learning applications that crunch, munge, and wrangle data collected from users, web applications, sensors, and website logs. Key machine learning concepts are explained and introduced with many code examples in Python's scikit-learn. The book guides readers through the underlying machinery and intelligent algorithms to capture, store, and structure data streams. Readers will explore recommendation engines from the example of Netflix movie recommendations and dive into classification via statistical algorithms, neural networks, and deep learning. They will also consider the ins and outs of ranking and how to test applications based on intelligent algorithms. KEY SELLING POINTS Machine learning for newbies Easily accessed examples Concepts presented are technology agnostic AUDIENCE To get the most from this book, you should have a good foundation in Java programming and a general understanding of internet technology. ABOUT THE TECHNOLOGY This book provides an overview, with easy to access examples, of algorithms which learn from data. Such algorithms have been widely adopted by many large internet companies such as Facebook and Google and are continuing to grow in popularity. This book has many examples in Python using the scikit-learn library, however the concepts presented are technology agnostic and can be easily applied with any common programming language.

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DESCRIPTION Project tracking systems, test and build tools, source control, continuous integration, and other built-in parts of the software development lifecycle generate a wealth of data that can be used to track and improve the quality and performance of products, processes, and teams. Although the iterative nature of Agile development is perfect for data-driven continuous improvement, the collection, analysis, and application of meaningful metrics often fades in favor of subjective measures that offer less insight into the real challenges of making better software. Continuous Improvement: Measuring and enhancing the performance of Agile teams is a practical book that shows how to take the data already being generated to make teams, processes, and products better. It points out which metrics to use to objectively measure performance and what data really counts, along with where to find it, how to get it, and how to analyze it. The book also shows how all team members can publish their own metrics through dashboards and radiators, taking charge of communicating performance and individual accountability. Along the way, it offers practical data analysis techniques, including a few emerging Big Data practices. KEY SELLING POINTS Straightforward to-the-point writing Contains techniques and tools to improve output Uses everyday examples to get readers up and running quickly Empowers and motivates Agile teams to measure and improve AUDIENCE The reader will ideally be on or be responsible for a team that is practicing Agile development or is about to begin using Agile development. ABOUT THE TECHNOLOGY All practices in this book are designed to work with any development process or tool stack. For its examples, this book uses the Groovy scripting language to gather data and Grails to create the web based dashboards and radiators. MongoDB, a flexible database with built in data analysis, is used to dissect and serve up the data.

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DESCRIPTION Kanban is an emerging second generation agile method inspired by five decades of process excellence in the Japanese auto manufacturing industry, also known as lean thinking. kanban uses visual management techniques that involve stakeholders and facilitates understanding of how the work works. It helps teams adjust demand to capacity, reduce lead times, and create a driver for continuous improvement. Kanban in Action is a down-to-earth, no-frills, get-to-know-the-ropes introduction to kanban. It's based on the real-world experience and observations from two kanban coaches who have introduced this process to dozens of teams. This book covers basic but powerful techniques on how to visualize and track work, construct a kanban board, and how to visualize queues and bottlenecks, and more. RETAIL SELLING POINTS  Down-to-earth introduction to Kanban  Practical advice for making workflow faster  Real-world case studies of Kanban at work AUDIENCE This book is written for all members of the development team, including leaders, coders, and business stakeholders. No experience with kanban is required. ABOUT THE TECHNOLOGY Kanban is an agile software development method for continuous collaborative improvement based on the lean principles of visualizing work, limiting the amount of work in process, and managing the flow of work.

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HIGHLIGHT The expert authors of Flex 4 in Action have one goal—to help readers get down to business with Flex 4. Fast. Updated with the latest features added in Flex 4. DESCRIPTION Flex 4 in Action is an easy-to-follow, hands-on Flex 4 tutorial. Revised and updated from the previous edition on Flex 3, this book is chock-full of examples, goes beyond feature coverage, and helps readers put Flex to work in real day-to-day tasks. This book helps Flex developers make their Flex applications stand out from the crowd. How comprehensive is Flex 4 in Action? • Interesting themes, styles, and skins? It’s in there. • Working with databases? You got it. • Interactive forms and validation? You bet. • Charting techniques to help you visualize data? Bam! Many Flex books are overwhelming to new users—focusing on the complexities of the language and super-specialized subjects in the Flex ecosystem. Flex 4 in Action filters out the noise and dives into the core topics users need every day. Using numerous easy-to-understand examples, Flex 4 in Action provides a strong foundation that readers can build on as the complexity of their projects increases. KEY POINTS • Expert authors have been working with Flex since the first version • Comprehensive yet easy to follow • Numerous do-this-every-day examples • Gets users ramped up and productive very quickly! • Makes the entry into using Flex fun, easy, and less scary This book is written for the millions of day-to-day web designers and developers who need to learn Flex to stay current.

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KEY POINTS• Accurate, practical techniques for SQL Server 2008 administration• Easy-to-use task-based reference format• Over 100 specific tips, procedures, and best practices SQL Server 2008 Administration isn’t a standard SQL Server tutorial—thereare dozens of those to choose from. Instead, this book breaks down the role of“SQL Server Administrator” into its key focus areas and tasks and details thetechniques and best practices that make an administrator effective.In this book, a reader can quickly identify a task and find the best practiceassociated with it. For example, a reader looking for information about indexingwould find step-by-step procedures for identifying and dropping unusedindexes, creating missing indexes, selecting the appropriate clustered index,and so forth.Each technique is presented in a clea

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HIGHLIGHT The expert authors of Flex 3 in Action have one goal—to help you get down to business with Flex 3. Fast. DESCRIPTION Flex 3 in Action is an easy-to-follow, hands-on Flex 3 tutorial. Chock-full of examples, this book goes beyond feature coverage and helps readers put Flex to work in real day-to-day tasks. This book helps Flex developers make their Flex applications stand out from the crowd. How comprehensive is Flex 3 in Action? • Interesting themes, styles, and skins? It’s in there. • Working with databases? You got it. • Interactive forms and validation? You bet. • Charting techniques to help you visualize data? Bam! Many Flex books are overwhelming to new users—focusing on the complexities of the language and super-specialized subjects in the Flex eco-system. Flex 3 in Action filters out the noise and dives into the core topics users need every day. Using numerous easy-to-understand examples, Flex 3 in Action provides a strong foundation that readers can build on as the complexity of their projects increases. KEY POINTS • Expert authors have been working with Flex since the first version • Comprehensive yet easy to follow • Numerous do-this-every-day examples • Gets users ramped up and productive very quickly! • Makes the entry into using Flex fun, easy, and less scary This book is written for the millions of day-to-day web designers and developers who need to learn Flex to stay current. MARKET INFORMATION New web applications require engaging user-friendly interfaces—and the cooler, the better. With Flex 3, web developers at any skill level can create high-quality, effective, and interactive Rich Internet Applications (RIAs) quickly and easily. Flex removes the complexity barrier from RIA development by offering sophisticated tools and a straightforward programming language so you can focus on what you want to do instead of how to do it. And now that the major components of Flex are free and open-source, the cost barrier is gone, as well!

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EJB 3 is the most important innovation introduced in Java EE 5.0. EJB 3 simplifiesenterprise development, abandoning the complex EJB 2.x model in favorof a lightweight POJO framework. The new API represents a fresh perspectiveon EJB without sacrificing the mission of enabling business application developersto create robust, scalable, standards-based solutions.EJB 3 in Action is a fast-paced tutorial, geared toward helping you learn EJB 3and the Java Persistence API quickly and easily. For newcomers to EJB, this bookprovides a solid foundation in EJB. For the developer moving to EJB 3 from EJB2, this book addresses the changes both in the EJB API and in the way the developershould approach EJB and persistence.

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HIGHLIGHT Open Source SOA shows readers how to build state-of-the-art SOA applications using freely-available open-source technologies. DESCRIPTION You can build a world-class SOA infrastructure entirely using popular, and mature, open-source applications. Unfortunately, the technical documentation for most open-source projects focuses on a specific product, the big SOA picture. You're left to your own devices to figure out how to cobble together a full solution from the various bits. In other words, unless you already know how Mule and Tuscany work with jBPM, you're stuck. Open Source SOA shows readers how to build an entire SOA application using open-source technologies. It shows readers how to apply key ideas like Enterprise Service Bus (ESB) design and Business Process Management (BPM) and learn the tools and techniques to implement them effectively. To pull everything together, the author describes real-life case studies from his own work to tie together all the principles and practices. These hard-to-find case studies are pure gold for the reader, as most developers keep these trade secrets to themselves. KEY POINTS • Theory—what SOA really represents • Enablers—SOA core technologies • Open-source applications that address the core technology • Best-of-breed open-source solutions • Real-life case studies MARKET INFORMATION SOA is a fact of life for enterprise developers. Open source technologies have caught up with—and in many cases, surpassed—their commercial rivals in terms of power, ease of use, and sophistication. This book shows a Java EE developer how to apply SOA techniques using the best-of-breed open-sources tools.

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　 DESCRIPTION Elixir is a functional programming language built on the Erlang virtual machine. It combines the productivity and expressivity of Ruby with the concurrency and fault-tolerance of Erlang. Elixir makes full use of Erlang's powerful OTP library, which many developers consider the source of Erlang's greatness, so programmers can have mature, professional-quality functionality right out of the gate. Elixir's support for functional programming makes it a great choice for highly distributed event-driven applications like IoT systems. The Little Elixir & OTP Guidebook gets readers programming applications with Elixir and OTP. First, it offers a quick overview of the Elixir language syntax, along with just enough functional programming to use it effectively. Then, it dives straight into OTP and shows how it helps build scalable, fault-tolerant, and distributed applications through several fun examples. Readers will rediscover the joy of programming with Elixir and remember what it feels like to be a beginner again. KEY FEATURES  Hand-on guide with fun examples  Gets readers building programs quickly  Brings back the joy of programming AUDIENCE Written for readers comfortable with a standard programming language like Ruby, Java, or Python. Experience with Erlang or another functional programming language is helpful. ABOUT THE TECHNOLOGY There is now a huge interest in functional programming languages such as Scala, Clojure, F#, Erlang and Haskell. Part of this reason is that these languages are better suited to exploit multi-core processors. Elixir is a functional programming language built on the Erlang virtual machine. It combines the productivity and expressivity of Ruby with the concurrency and fault-tolerance of Erlang.

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This fully revised second edition of Machine Learning with TensorFlow teaches you the foundational concepts of machine learning and how to utilize the TensorFlow library to rapidly build powerful ML models. You’ll learn the basics of regression, classification, and clustering algorithms, applying them to solve real-world challenges. New and revised content expands coverage of core machine learning algorithms and advancements in neural networks such as VGG-Face facial identification classifiers and deep speech classifiers. Written by NASA JPL Deputy CTO and Principal Data Scientist Chris Mattmann, all examples are accompanied by downloadable Jupyter Notebooks for a hands-on experience coding TensorFlow with Python. Key Features · Visualizing algorithms with TensorBoard · Understanding and using neural networks · Reproducing and employing predictive science · Downloadable Jupyter Notebooks for all examples · Questions to test your knowledge · Examples use the super-stable 1.14.1 branch of TensorFlow Developers experienced with Python and algebraic concepts like vectors and matrices. About the technology TensorFlow, Google’s library for large-scale machine learning, makes powerful ML techniques easily accessible. It simplifies often-complex computations by representing them as graphs that are mapped to machines in a cluster or to the processors of a single machine. Offering a complete ecosystem for all stages and types of machine learning, TensorFlow’s end-to-end functionality empowers machine learning engineers of all skill levels to solve their problems with ML. Chris Mattmann is the Deputy Chief Technology and Innovation Officer at NASA Jet Propulsion Lab, where he has been recognised as JPL's first Principal Scientist in the area of Data Science. Chris has applied TensorFlow to challenges he’s faced at NASA, including building an implementation of Google’s Show & Tell algorithm for image captioning using TensorFlow. He contributes to open source as a former Director at the Apache Software Foundation, and teaches graduate courses at USC in Content Detection and Analysis, and in Search Engines and Information Retrieval. Nishant Shukla wrote the first edition of Machine Learning with TensorFlow.

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Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms. Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process. Key Features · Active Learning to sample the right data for humans to annotate · Annotation strategies to provide the optimal interface for human feedback · Supervised machine learning design and query strategies to support Human-in-the-Loop systems · Advanced Adaptive Learning approaches · Real-world use cases from well-known data scientists For software developers and data scientists with some basic Machine Learning experience. About the technology “Human-in-the-Loop machine learning” refers to the need for human interaction with machine learning systems to improve human performance, machine performance, or both. Ongoing human involvement with the right interfaces expedites the efficient labeling of tricky or novel data that a machine can’t process, reducing the potential for data-related errors. Robert Munro has built Annotation, Active Learning, and machine learning systems with machine learning-focused startups and with larger companies including Amazon, Google, IBM, and most major phone manufacturers. If you speak to your phone, if your car parks itself, if your music is tailored to your taste, or if your news articles are recommended for you, then there is a good chance that Robert contributed to this experience. Robert holds a PhD from Stanford focused on Human-in-the-Loop machine learning for healthcare and disaster response, and is a disaster response professional in addition to being a machine learning professional. A worked example throughout this text is classifying disaster-related messages from real disasters that Robert has helped respond to in the past.

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Description Microservices are independent, single-responsibility units of code that form a system with other microservices. It's difficult to test an individual microservice since each one depends on the other services. Mountebank solves this conundrum through service virtualization - imitating other components in the system so that you can test a microservice in isolation. Testing Microservices with Mountebank is your guide to the ins and outs of testing microservices with service virtualization. This book also explains using mountebank for load testing, in a continuous delivery pipeline, and more. Key features · Hands-on examples · Step-by-step guide · Clearly written Audience Readers need programming skills and should be generally familiar with SOA or microservice systems. About the technology Mountebank is the most capable service virtualization tool around, providing a programmable stand-in for a real dependency. As the only open-source virtualization tool with support for multiple protocols and scaling for load testing mountebank isn't snake oil; it's the cure-all for all your service virtualization needs. Author biography Brandon Byars is a principal consultant at ThoughtWorks with longstanding experience in SOA and microservices. He is the author and chief maintainer of Mountebank and has helped multiple companies use it for testing a variety of systems.

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Description The Angular 2 framework is great for building large-scale web applications that can be maintained and extended. And when building enterprise-level apps, testing is vital to the development process. Testing improves the quality of code and reduces maintenance, saving both time and money. Even though testing is crucial, it’s sometimes neglected since there are few established resources and standards when it comes to modern JavaScript web applications. Developers who know how to build and leverage tests are highly valued by their clients and companies. Testing Angular Applications is an example-rich, hands-on guide that gives the real-world techniques needed to thoroughly test all parts of Angular 2 applications. The book starts with an introduction to Angular 2, TypeScript, testing fundamentals, and the testing frameworks and tools used in the book. Next, it explains how to set-up an Angular 2 environment, including TypeScript and the Angular 2 dependencies. The reader will then create their first component. The second part of the book focuses on the most important concepts of Angular 2, such as testing components, directives, pipes, services, and routing. This book will allow readers to confidently write unit and endto-end tests for Angular 2 applications and TypeScript. Key features • Testing components, directives, services and pipes • Real-world techniques • Hands-on examples • Foundation for writing advances tests • Provides code that can be reused in a production environment Audience This book is for readers with intermediate JavaScript skills and some experience with JavaScript frameworks. No experience with testing or Angular required. About the Technology Angular 2 is the latest version of the popular web application framework built by Google and its army of community contributors. Angular 2 is a mobile-first framework that promises to be fast, flexible, and expressive. The Angular 2 syntax is clean and easy to read, which lends itself nicely to rapid development and assists in writing tests.

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DESCRIPTION The modern "data center" is a complex arena, with physical and virtual servers, multiple OS environments, and complex networking that frequently spans multiple locations. The need to simplify has never been greater. Mesos, an innovative open-source cluster management platform, transforms the whole data center into a single pool of compute, memory, and storage resources that can be allocated, automated, and scaled as if working with a single super-computer. Mesos is an ideal environment for deploying containerized applications at scale, and it's generating a huge buzz in the big data world as a saner environment for running Spark and Hadoop. Mesos in Action introduces the Apache Mesos cluster manager and the concept of application-centric infrastructure. It guides readers from their first steps in deploying a highly-available Mesos cluster through deploying applications in production and writing native Mesos frameworks. It will show how to scale to thousands of nodes, while providing resource isolation between processes using Linux and Docker containers. It contains practical techniques for deploying applications using popular key frameworks, including Marathon, Chronos, and Aurora. Along the way, the book dives into Mesos internals, including fault tolerance, slave attributes, and resource scheduling and Mesos administration, including logging, monitoring, framework authorization, and slave recovery. KEY FEATURES  Gets readers up and running quickly  Covers need to know key concepts  Combines community knowledge with real-world experience AUDIENCE Readers should be familiar with the core ideas of data center administration, including networking, virtualization, and application deployment on Linux systems. The Python-based code examples should be clear to readers using Mesos bindings for other popular languages, including C++, Go, and Scala. ABOUT THE TECHNOLOGY Apache Mesos is clustering software that allows IT professionals to abstract datacenter resources – CPU, memory, and storage – away from physical and virtual infrastructure and into a Mesos cluster. This allows software developers to write applications that use entire data centers as if they were a single, large computer.

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　 DESCRIPTION Windows administrators will want this book open on their desk most of the time. With over 40 short chapters, each focused on a specific area of PowerShell, they’ll be able to find answers fast. Each valuable technique was developed and thoroughly tested by seasoned PowerShell experts, so they’ll be able to consistently produce production quality, maintainable scripts that will save countless hours of time and effort. PowerShell in Depth, Second Edition is the go-to reference for administrators working with Windows PowerShell. Every major technique, technology, and tactic is carefully explained and demonstrated, providing a hands-on guide to almost everything an admin would do in the shell. Written by three experienced authors and PowerShell MVPs, this is the PowerShell book readers will keep next to their monitors—not on their bookshelf! 　 RETAIL SELLING POINTS Provides in-depth coverage of PowerShell Written by acknowledged world class PowerShell experts Shows how to solve real-world administrative problems AUDIENCE This book assumes readers know the basics of PowerShell. ABOUT THE TECHNOLOGY PowerShell is an automation engine for Windows systems. It is being built into all major Microsoft products and many third party products. PowerShell allows for the automations of day to day administration tasks and is a must learn technology for administrators.

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　 It's a lot harder to make sense out of data when it's coming at full speed. Apache Storm’s efficient stream processing capabilities are relied upon by giants like Twitter and Yahoo for swiftly extracting intelligence from their Big Data streams. Fault tolerant guarantees of Storm make it an invaluable and versatile platform in the Big Data landscape. It integrates seamlessly with battle-tested message queuing systems (like Kafka) and NoSQL databases (like Cassandra). Storm is built to run on the JVM but provides straightforward extensions for working with non-JVM languages like Ruby and Python. Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams. The book starts by building a solid foundation of the Storm essentials. Then, it quickly dives into real-world case studies that will bring the novice up to speed with productionizing Storm: the knowledge needed to scale a high throughput stream processor and ensure smooth operation within a production cluster. It moves on to teach readers how to use Trident to treat streams as batches for solving a different class of problems, and covers the tools available within the Storm open source community that are crucial for any seasoned Storm developer. 　 RETAIL SELLING POINTS Immediately useful practical guide Applies Storm to real-world use cases Takes Storm from development to a fully tuned and optimized production setup AUDIENCE While prior experience with Storm is not necessary, acquaintance with related Big Data problem solving is helpful. Basic understanding of Java or similar JVM language and concurrency is assumed. DESCRIBE THE TECHNOLOGY Storm is a tool that can be used for processing "big data" in real-time. Think performing real-time analysis of all the tweets going through Twitter.

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DESCRIPTION Ruby on Rails is an open source web framework. It's famously simple to build a basic Rails application. Once you've started down the track, however, you discover that Rails is a powerful, deep, and rich full-stack platform capable of tackling virtually any development challenge. Rails 4 in Action is a fully-revised second edition of Rails 3 in Action. This hands-on, comprehensive introduction to Rails gives readers everything they need to become competent and confident Rails developers. It shows how to develop a ticket tracking application that includes RESTful routing, authentication and authorization, file uploads, email, and more. It explores powerful features like designing APIs and building a Rails engine. The book also provides Test Driven Development and Behavior Driven Development in action throughout the book—just like in a top Rails shop. RETAIL SELLING POINTS Fully updated for Rails 4 New and improved testing examples More options for creating APIs Written by Rails community leaders AUDIENCE It is helpful for readers to have a background in Ruby, but no prior Rails experience is needed. ABOUT THE TECHNOLOGY Ruby on Rails, often called Rails, is an open source web framework for the Ruby programming language. It’s a full-stack platform capable of tackling virtually any development challenge.

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Revolutionize the way your organization approaches data with a data mesh! This new decentralized architecture outpaces monolithic lakes and warehouses and can work for a company of any size. Data Mesh in Action reveals how this ground breaking architecture looks for both small start-ups and large enterprises. You'll see a datamesh in action as you explore both an extended case study andmultiple real-world examples. As you go, you'll be expertly guidedthrough discussions around Socio-Technical Architecture and Domain-Driven Design with the goal of building a sleek data-as-a-productsystem.

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Well-designed applications run more efficiently, have fewer bugs, and are easier to revise and maintain. Learn the fundamentals of Object-Oriented Design by investigating good and bad code.Using an engaging before-and-after approach, Object-Oriented Software Design in C++ shows you exactly what bad software looks like and how to fix it with good design principles and patterns. In it, you''ll find: Design-code-test iterations that improve code with each revision Gathering requirements to make sure you''re developing the right application Design principles like encapsulation and delegation that solve programming problems Design patterns including Observer Design Pattern that fix architecture issues Using recursion and multithreading to simplify common solutions

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In 2017, consumers downloaded 178 billion apps, and analysts predict growth to 258 billion by 2022. Mobile customers are demanding more—and better—apps, and it’s up to developers like you to write them! Flutter, a revolutionary new cross-platform software development kit created by Google, makes it easier than ever to write secure, high-performance native apps for iOS and Android. Flutter in Action teaches you to build awesome, full-featured mobile applications with Flutter. Author Eric Windmill walks with you every step of the way as you build apps that get you coding as you learn. With the engaging hands-on examples, you’ll create a basic user interface, learn about state management, and integrate a database with a Dart web app. Key features • Understanding the basic Flutter UI • Integrating platform-specific functionality for iOS and Android • Building layouts in Flutter • Testing and debugging Audience For developers familiar with the basics of programming web applications. No experience with Dart or Flutter needed! About the technology Flutter apps are blazingly fast because this open source solution compiles your Dart code to platform-specific programs with no JavaScript bridge! Flutter also supports hot reloading to update changes instantly. And thanks to its built-in widgets and rich motion APIs, Flutter’s apps are not just highly responsive, they’re stunning! Eric Windmill is a professional Dart developer, a contributor to opensource Flutter projects, and the author of FlutterByExample.com. His work is featured on Flutter’s own showcase page, https://flutter.io/showcase.

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Kubernetes Quickly is a clear and practical beginner's guide that shows you just how easy, flexible, and cost-effective it can be to make the switch to Kubernetes deployment even for small to medium-sized applications. Kubernetes Quickly is a hands-on guide to taking your first steps into Kubernetes using the powerful Google Kubernetes Engine service. It lays out a map for taking an application, containerizing it, and then deploying it onto Kubernetes. You'll learn best practice techniques for a stable and long-term Kubernetes deployment, including scaling and capacity planning, saving money by optimizing resource consumption, and tricks to make your day-to-day monitoring easier such as debugging code in the cloud. You don't need to incur huge costs or have the manpower of an enterprise organization to get a productivity boost from Kubernetes. By organizing your application component into containerized components and automating tasks like scaling and replication, Kubernetes keeps your apps running smoothly. Cloud-based Kubernetes services like Google Kubernetes Engine(GKE) reduce OS issues, simplify operations, and give you the freedom to use whatever software stack you want. If you've heard that switching to Kubernetesis complex, good news—Kubernetes for Developers will show you how it can be done without a time-consuming rebuild. Using examples from the Google Kubernetes Engine created by the team who invented Kubernetes itself, you'll learn to set up future-proof application deployments that scale to handle ever-growing and complex workloads.

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Description Microservices promise a better way to sustainably deliver business impact. Rather than a single monolithic unit, applications built in this style are composed from loosely-coupled, autonomous services. Microservices in Action is a practical book about building and deploying microservice-based applications. Written for developers and architects with a solid grasp of service-oriented development, it tackles the challenge of putting microservices into production. Key features · Review of microservice architecture · Written by authors with daily, hands-on experience · Building a delivery pipeline for microservices Audience Readers should be intermediate developers with some knowledge of enterprise application architecture. About the technology Microservices change the dev process, maximizing the efficiency and independence of small teams. To be successful, developers, team leaders, and architects need to master both the implementation details and the big picture of how microservices work in a production environment. Morgan Bruce and Paulo A. Pereira have years of experience building distributed applications, with particular expertise in the high-stakes finance and identity verification industries. They work daily with microservices in a production environment using the tools and techniques presented in this book.

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Developing applications in a reactive style ensures that the experience is always responsive. Akka.NET is a framework for building distributed, message-driven applications which are able to stay responsive for the user even in the face of failure or when faced with more users. It makes it easy for .NET developers to write applications which are able to react to changes in their environment. Reactive Applications with Akka.NET begins with an overview of reactive and a sample application written in the reactive style. Readers will learn concepts of the actor model and what these mean in a realworld reactive context. This hands-on book builds on fundamental concepts that teach how to create reliable and resilient applications. It also teaches useful Akka.NET features for building real-world applications. By the end of the book, readers will be able to look at a problem domain and understand how to create applications which are able to withstand modern demands. Key features: • Hands-on examples that build on fundamental concepts • Building real-world applications with Akka.NET • Designing an Internet of Things architecture with reactive in mind • How to create applications that can withstand modern demands AUDIENCE Readers should be comfortable with C# or F# and the .NET framework. No previous reactive experience needed. ABOUT THE TECHNOLOGY Developing applications in a reactive style ensures that the experience is always responsive. Akka.NET is a framework for building distributed, message-driven applications which are able to stay responsive for the user even in the face of failure or when faced with more users.

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Pandas has rapidly become one of Python's most popular data analysis libraries. With pandas you can efficiently sort, analyze, filter and munge almost any type of data. In Pandas in Action, a friendly and example-rich introduction, author Boris Paskhaver shows you how to master this versatile tool and take the next steps in your data science career. about the technologyAnyone who’s used spreadsheet software will find pandas familiar. While its column-based grids might remind you of Excel or Google Sheets, pandas is more flexible and far more powerful. It can efficiently perform operations on millions of rows and be used in tandem with other Python libraries for statistics, machine learning, and more. And best of all, using pandas doesn’t mean sacrificing user productivity or needing to write tons of complex code. It’s clean, intuitive, and fast. about the book Pandas in Action makes it easy to dive into Python-based data analysis. You’ll learn to use pandas to automate repetitive spreadsheet functionality and derive insight from data by sorting columns, filtering data subsets, and creating multi-leveled indices. Each chapter is a self-contained tutorial, letting you dip in when you need to troubleshoot tricky problems. Best of all, you won’t be learning from sterile or randomly created data. You’ll start with a variety of datasets that are big, small, incomplete, broken, and messy and learn how to clean and format them for proper analysis. what's inside Import a CSV, identify issues with its data structures, and convert it to the proper format Sort, filter, pivot, and draw conclusions from a dataset and its subsets Identify trends from text-based and time-based data Organize, group, merge, and join separate datasets Real-world datasets that are easy to download and explore about the readerFor readers experienced with spreadsheet software who know the basics of Python. about the author Boris Paskhaver is a software engineer, Agile consultant, and educator. His six programming courses on Udemy have amassed 236,000 students, with an average course rating of 4.59 out of 5. He first used Python and the pandas library to derive a variety of business insights at the world’s #1 jobs site, Indeed.com.

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Develop a mathematical intuition around machine learning algorithms to improve model performance and effectively troubleshoot complex ML problems. For intermediate machine learning practitioners familiar with linear algebra, probability, and basic calculus. Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you will learn the fundamentals of Bayesian inference and deep learning. You will also explore the core data structures and algorithmic paradigms for machine learning. You will explore practical implementations of dozens of ML algorithms, including: Monte Carlo Stock Price Simulation Image Denoising using Mean-Field Variational Inference EM algorithm for Hidden Markov Models Imbalanced Learning, Active Learning and Ensemble Learning Bayesian Optimisation for Hyperparameter Tuning Dirichlet Process K-Means for Clustering Applications Stock Clusters based on Inverse Covariance Estimation Energy Minimisation using Simulated Annealing Image Search based on ResNet Convolutional Neural Network Anomaly Detection in Time-Series using Variational Autoencoders Each algorithm is fully explored with both math and practical implementations so you can see how they work and put into action. About the technology Fully understanding how machine learning algorithms function is essential for any serious ML engineer. This vital knowledge lets you modify algorithms to your specific needs, understand the trade-offs when picking an algorithm for a project, and better interpret and explain your results to your stakeholders. This unique guide will take you from relying on one-size-fits-all ML libraries to developing your own algorithms to solve your business needs.

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From its humble beginnings a container orchestration system, Kubernetes has become the de facto infrastructure for cloud native applications. Kubernetes impacts every aspect of the application development lifecycle, from design through deployment. To build and operate reliable cloud native systems, you need to understand what's going on below the surface. Core Kubernetes is packed with experience-driven insights and practical techniques, and takes you inside Kubernetes to teach you what you'll need to know to keep your system running like a well-oiled machine and prevent those panicked 3 AM phone calls. about the technologyKubernetes is a platform-independent layer for deploying scalable container-based applications. Kubernetes provides abstractions for clustering, replicating, and scaling system components in real time. It's especially well-suited for microservices applications, where you can easily balance the load among services. Kubernetes has become a core component of cloud native applications, and all major cloud vendors now offer hosted versions of Kubernetes. Kubernetes was initially developed by Google and is now governed as an open source project by the Cloud Native Computing Foundation (CNCF). about the bookCore Kubernetes is a reference guide designed to teach operators, SREs, and developers how to improve reliability and performance of Kubernetes-based systems. In it, Kubernetes experts Chris Love and Jay Vyas provide a guided tour through all major aspects of Kubernetes, from managing iptables to setting up dynamically scaled clusters that respond to changes in load. You'll understand the unique security concerns of container-based applications, discover tips to minimize costly unused capacity, and get pro tips for maximizing performance. This awesome collection of undocumented internals, expert techniques, and practical guidance has invaluable information you won't find anywhere else. what's inside- Kubernetes base components- Kubernetes networking- Storage and the Container Storage Interface- External load balancing and ingress- Kubernetes security- Different ways of creating a Kubernetes cluster- Configuring Kubernetes to use a GPU about the readerWritten for readers with a working knowledge of Kubernetes and microservices applications. about the authorAfter earning his PhD, Jay Vyas started his career contributing to Kubernetes' core features at RedHat, and next, he focused on helping multiple companies migrate to Cloud-Native solutions. He now resides at VMWare, once again contributing to Kubernetes and associated projects. When not coding, Jay likes to play with his video games, his synthesizers, and hang out in his Pod. As a thought leader in the Kubernetes and DevOps segment, Chris Love is a founder of multiple technology companies with over 20 years' experience in software engineering. A Google Cloud Certified Fellow, Chris has contributed to several open-source projects including Kubernetes, Bazel, and Terraform. He enjoys speaking around the world about DevOps and Kubernetes and practices martial arts in his free time.

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This friendly, fast-paced guide is perfect for anyone puzzled by the cloud! Learn the fundamentals of Amazon Web Services, and be ready to ace your AWS Certified Cloud Practitioner Exam. In AWS for Non-engineers you will learn: How cloud computing and AWS are different from “legacy” systems Prepare for the AWS Certified Cloud Practitioner Exam When cloud computing is the right option for your organization Core AWS services including storage services, database services, and security services How billing and pricing work on AWS, and how to pick for your budget Security and compliance concepts for building in AWS AWS for Non-engineers is written for anyone just starting with Amazon Web Services or cloud computing in general. It's written by Hiroko Nishimura, and is based on her acclaimed video course that has been taken by over 250,000 learners. In this reader-friendly book, you'll learn how to talk about cloud concepts with engineers, what the cloud could do for your business, and how to start using AWS's amazing services for your own IT tasks. When you're finished, you'll be comfortable with the basics of cloud computing on AWS and you'll be prepared to take the AWS Certified Cloud Practitioner Exam! about the technology Modern IT systems run in the cloud. Whether you're in customer service, marketing, or a technical role, cloud technologies like Amazon Web Services (AWS) have become as important to your job as spreadsheets, CRMs, and databases. Knowing AWS fundamentals will help you speak the language of developers and software engineers, and eventually create your own products, services, and projects.

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Effective Software Testing is a hands-on guide to creating high quality tests, from your first line of code through pre-delivery checks. It's full of techniques drawn from proven research in software engineering. You'll learn to efficiently engineer tests specifically for your software and end reliance on generic testing practices that may be right for every project. Each chapter puts a new technique into practice with source code samples, real-world tradeoffs, and answers to the common questions developers pose about testing. You'll learn how to scrutinize your requirements for potential tests, generate tests from your code structure, and engineer rigorous suites of unit, integration, and system tests. Go beyond unit tests! Great software testing makes the entire development process more efficient, from understanding your code before you write it to catching bugs in tricky corner cases.Effective Software Testing teaches you a systematic approach to software testing. You'll master easy-to-apply techniques to create strong test suites that are specifically engineered for your code. Following real-world use cases and detailed code samples, you'll soon be engineering tests that find the bugs hiding in edge cases and the parts of code you would never think of testing! Along the way, you'll develop an intuition for testing that can save years of learning by trial and error.

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Explore the fascinating and rich world of Secret Key cryptography! This book provides practical methods for encrypting messages, an interesting and entertaining historical perspective, and an incredible collection of ciphers and codes—including 30 unbreakable methods. In Secret Key Cryptography: Ciphers, from simple to unbreakable you will: Measure the strength of your ciphers and learn how to guarantee their security Construct and incorporate data-compression codes Generate true random numbers in bulk Construct huge primes and safe primes Add an undetectable backdoor to a cipher Defeat hypothetical ultracomputers that could be developed decades from now Construct 30 unbreakable ciphers Secret Key Cryptography gives you a toolbox of cryptographic techniques and Secret Key methods. The book's simple, non-technical language is easy to understand and accessible for any reader, even without the advanced mathematics normally required for cryptography. You'll learn how to create and solve ciphers, as well as how to measure their strength. As you go, you'll explore both historic ciphers and groundbreaking new approaches—including a never-before-seen way to implement the uncrackable One-Time Pad algorithm. about the technology Secret Key cryptography is the backbone of all modern computing infrastructure. Secret Key ciphers use the same key to encrypt and decrypt messages. Properly designed, these algorithms are efficient and practical. Some Secret Key approaches are uncrackable, even under attacks backed by supercomputers or quantum technology! about the book Secret Key Cryptography teaches anyone how to create a wide range of ciphers—even if you have no background in math or creating codes. You'll combine Secret Key techniques to achieve ciphers that are effectively uncrackable and avoid common pitfalls that result in strong-looking but weak ciphers. The book reveals scores of different cipher methods, including both historic examples and current innovations in the field. RETAIL SELLING POINTS • Measure the strength of your ciphers and learn how to guarantee their security • Construct and incorporate data-compression codes • Generate true random numbers in bulk • Construct huge primes and safe primes • Add an undetectable backdoor to a cipher • Defeat hypothetical ultra computers that could be developed decades from now • Construct 30 unbreakable ciphers AUDIENCE For professional engineers, computer scientists, and cryptography hobbyists. No advanced math knowledge is required

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Master core data analysis skills using Julia. Julia for Data Analysis is a fascinating, hands-on projects guide you through time series data, predictive models, popularity ranking, and more. With this book, you will learn how to: Read and write data in various formats Work with tabular data, including subsetting, grouping, and transforming Visualise your data using plots Perform statistical analysis Build predictive models Create complex data processing pipelines Julia was designed for the unique needs of data scientists: it's expressive and easy-to-use whilst also delivering super fast code execution. Julia for Data Analysis teaches you how to perform core data science tasks with this amazing language. It is written by Bogumił Kamiński, a top contributor to Julia, #1 Julia answerer on StackOverflow, and a lead developer of Julia's core data package DataFrames.jl. You will learn how to write production-quality code in Julia, and utilize Julia's core features for data gathering, visualisation, and working with data frames. Plus, the engaging hands-on projects get you into the action quickly. About the technology Julia is a huge step forward for data science and scientific computing. It is a powerful high-performance programming language with many developer-friendly features like garbage collection, dynamic typing, just-in-time compilation, and a flexible approach to concurrent, parallel, and distributed computing. Although Julia's strong numerical programming features make it a favorite of data scientists, it is also an awesome general purpose programming language. About the reader For data scientists familiar with Python or R. No experience with Julia required.

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Learn how to build fast and secure gRPC-based microservices using the powerful Go programming language. Ideal for software developers who know the basics of Go. gRPC Microservices in Go shows you howto combine the powerful gRPC Remote Procedure Call framework with Golang's low-level efficiency and flexibility. You will learn how to develop microservice inter-service communication patterns powered by gRPC, design backwards compatible APIs, and apply hexagonal architecture to microservices. Key features: Designing and implementing a resilient microservice architecture Testing microservices Deploying microservices to the cloud with modern orchestration tools Monitoring and overseeing microservices The powerful gRPC Remote Procedure Call framework delivers superior speed and security over protocols like REST. When paired with Golang's low-level efficiency and flexibility, gRPC and Go become a killer combination for latency-sensitive microservices applications. gRPC Microservices in Go shows you how to utilise these powerful tools to build production-grade microservices. About the technology Initially developed by Google, gRPC is a high-performance messaging protocol that is extraordinarily well-suited for microservices applications. This open-source framework helps you elegantly and reliably deliver messages securely within a microservices architecture. Its seamless integration with infrastructure for load balancing, tracing, fault tolerance, and security helps you effortlessly solve many of the common challenges of microservices. gRPC's server and client stubs let your project call remote service methods and define the business logic behind them. Combined with Go's fast compilation and execution speed, it's the perfect solution for building large-scale microservices architectures.

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Build your skills with essential modern C++ features hands-on by completing eight interesting coding projects. In Learn C++ by Example you''ll: Learn how to write modern C++ using new features from C++ 11 to 23 Think about testing as you code Learn what happens under the hood of your C++ code Choose the most efficient algorithm or data structure About the technology C++ is used for everything from financial modeling to video games. C++ 11, 17, and 20 have all introduced exciting features that can increase your coding efficiency. This book introduces these features by putting them to use in real projects. Along the way, you''ll get up to speed with frequently used data structures, algorithms, and various parts of the standard library.

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Master the demand forecasting skills you need to decide what resources to acquire, products to produce, and where and how to distribute them. For demand planners, S&OP managers, supply chain leaders, and data scientists. Demand Forecasting Best Practices is a unique step-by-step guide, demonstrating forecasting tools, metrics, and models alongside stakeholder management techniques that work in a live business environment. You will learn how to: Lead a demand planning team to improve forecasting quality while reducing workload Properly define the objectives, granularity, and horizon of your demand planning process Use smart, value-weighted KPIs to track accuracy and bias Spot areas of your process where there is room for improvement Help planners and stakeholders (sales, marketing, finances) add value to your process Identify what kind of data you should be collecting, and how Utilise different types of statistical and machine learning models Follow author Nicolas Vandeput's original five-step framework for demand planning excellence and learn how to tailor it to your own company's needs. You will learn how to optimise demand planning for a more effective supply chain and will soon be delivering accurate predictions that drive major business value. About the technology Demand forecasting is vital for the success of any product supply chain. It allows companies to make better decisions about what resources to acquire, what products to produce, and where and how to distribute them. As an effective demand forecaster, you can help your organisation avoid overproduction, reduce waste, and optimise inventory levels for a real competitive advantage.

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Create Python packages to share your code in a scalable and maintainable way. Improve team productivity, publish helpful libraries, or even start your own open source project following the latest Python packaging standards. In Publishing Python Packages you will learn how to: Build extensions and console script commands Use tox to automate packaging, installing, and testing Build a continuous integration pipeline using GitHub Actions Improve code quality and reduce manual review using bandit, black, mypy, and radon Create published documentation for your packages Keep packages up to date with pyupgrade and Dependabot Foster an open source community using GitHub features Publishing Python Packages teaches you how to easily share your Python code with your team and the outside world. Learn a repeatable and highly automated process for package maintenance that's based on the best practices, tools, and standards of Python packaging. Whether you're entirely new to Python packaging or looking for optimal ways to maintain and scale your packages, this fast-paced and engaging guide is for you. about the technology Python packages are a great way to share your code and give a productivity boost to your colleagues and community. Whether you're reusing your code internally or contributing to open source, a properly automated system of packaging will save you from time-consuming manual maintenance. about the book Publishing Python Packages reveals best practices and standards for packaging your Python code in an easy, automated, and scalable way. The book walks you through creating a complete package, including a C extension, and guides you all the way to publishing on the Python Package Index. You'll get hands-on experience with the latest packaging tools, and learn the ins-and-outs of package testing and continuous integration. You'll even learn how to set up a successful open source project, including licensing, documentation, and nurturing a community of contributors.

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Learn Julia programming by building fun projects, like launching rockets, building password keepers, and even coding battle simulations. Julia as a Second Language covers: How Julia implements data types such as numbers, strings, arrays, and dictionaries Solving problems with both object-oriented and functional programming Getting immediate feedback with Julia's read-evaluate-print-loop (REPL) Taking advantage of Julia's powerful multiple dispatch system Sharing code using modules and packages Julia as a Second Language introduces Julia to readers with a beginning-level knowledge of another language like Python or JavaScript. It skips programming basics and dives straight into Julia's unique features. You'll learn by coding engaging hands-on projects that encourage you to apply what you are learning immediately. About the technology Julia is a powerful high-performance programming language with many developer-friendly features like garbage collection, dynamic typing, just-in-time compilation, and a flexible approach to concurrent, parallel, and distributed computing. Although Julia's strong numerical programming features make it a favorite of data scientists, it is also an awesome general purpose programming language. Julia's users call it the "goldilocks language", with a "just right" balance of performance and productivity. About the reader Readers need basic skills with another programming language like Python, JavaScript, or C#.

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Safely store secret information like passwords, keys, and certificates in Kubernetes. In this practical guide, you'll discover methods for adding layers of security that will defend the critical data of your applications.In Securing Kubernetes Secrets you will find: Strategies for storing secure assets in Kubernetes Cryptographic options and how to apply them in Kubernetes Using the HashiCorp Vault server on Kubernetes for secure secrets storage Managing security with public cloud providers Applying security concepts using tools from the Kubernetes ecosystem End-to-end secrets storage from development to operations Implementing in Kubernetes in CI/CD systems Secrets, like database passwords and API keys, are some of the most important data in your application. Securing Kubernetes Secrets reveals how to store these sensitive assets in Kubernetes in a way that's protected against leaks and hacks. You'll learn about the default capabilities of Kubernetes secrets, where they're lacking, and alternative options to strengthen applications and infrastructure. Kubernetes secrets include small and sensitive data like passwords, tokens, and keys. The security defaults of Kubernetes are rarely enough to protect this valuable data, and can leave it—and you—exposed. In this book, you'll learn how to bake security into Kubernetes-based applications right from the start with security best practices and reliable third-party tools like HashiCorp Vault

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A jargon-free, practical guide to the key concepts, terminology, and technologies of cybersecurity perfect for anyone planning or implementing a security strategy. Go behind the headlines of famous attacks and learn lessons from real-world breaches that author Tom Kranz has personally helped to clean up. Making Sense of Cyber Security is full of clear-headed advice and examples that will help you identify risks in your organization and choose the right path to apply the important security concepts effectively. Making Sense of Cyber Security is a no-nonsense overview of common cyber threats. Written for readers at all skill levels, this easy-to-read guide breaks down the core ideas and terminology of cybersecurity so that you can effectively contribute to the planning and implementation of a security strategy. You'll learn the three pillars of a successful security strategy and how to create and apply threat models that will iteratively improve your organization's readiness about the technology Every high-profile data breach underlines the need for cybersecurity. A proper understanding of threats, vulnerabilities, and most-likely attacks empowers you to make better decisions and mitigate risks. about the book Making Sense of Cyber Security is a no-nonsense overview of common cyber threats. Written for readers at all skill levels, this easy-to-read guide breaks down the core ideas and terminology of cybersecurity so that you can effectively contribute to the planning and implementation of a security strategy. You'll learn the three pillars of a successful security strategy and how to create and apply threat models that will iteratively improve your organization's readiness. Renowned security expert Tom Kranz teaches you to think like a hacker, ensuring you can spot your own weak points and evaluate risks in new technologies or processes. You'll cement this mindset by planning your own penetration test—taking on the role of the attacker in a simulated hack against an asset management firm. Finally, you'll work through a real-world security breach, learning how to respond to live threats and apply the lessons learned to your own organization.

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Deploying a machine learning model into a fully realized production system usually requires painstaking work by an operations team creating and managing custom servers. Cloud Native Machine Learning helps you bridge that gap by using the pre-built services provided by cloud platforms like Azure and AWS to assemble your ML system’s infrastructure. Following a real-world use case for calculating taxi fares, you’ll learn how to get a serverless ML pipeline up and running using AWS services. Clear and detailed tutorials show you how to develop reliable, flexible, and scalable machine learning systems without time-consuming management tasks or the costly overheads of physical hardware. about the technologyYour new machine learning model is ready to put into production, and suddenly all your time is taken up by setting up your server infrastructure. Serverless machine learning offers a productivity-boosting alternative. It eliminates the time-consuming operations tasks from your machine learning lifecycle, letting out-of-the-box cloud services take over launching, running, and managing your ML systems. With the serverless capabilities of major cloud vendors handling your infrastructure, you’re free to focus on tuning and improving your models. about the book Cloud Native Machine Learning is a guide to bringing your experimental machine learning code to production using serverless capabilities from major cloud providers. You’ll start with best practices for your datasets, learning to bring VACUUM data-quality principles to your projects, and ensure that your datasets can be reproducibly sampled. Next, you’ll learn to implement machine learning models with PyTorch, discovering how to scale up your models in the cloud and how to use PyTorch Lightning for distributed ML training. Finally, you’ll tune and engineer your serverless machine learning pipeline for scalability, elasticity, and ease of monitoring with the built-in notification tools of your cloud platform. When you’re done, you’ll have the tools to easily bridge the gap between ML models and a fully functioning production system. what's inside Extracting, transforming, and loading datasets Querying datasets with SQL Understanding automatic differentiation in PyTorch Deploying trained models and pipelines as a service endpoint Monitoring and managing your pipeline’s life cycle Measuring performance improvements about the readerFor data professionals with intermediate Python skills and basic familiarity with machine learning. No cloud experience required. about the author Carl Osipov has spent over 15 years working on big data processing and machine learning in multi-core, distributed systems, such as service-oriented architecture and cloud computing platforms. While at IBM, Carl helped IBM Software Group to shape its strategy around the use of Docker and other container-based technologies for serverless computing using IBM Cloud and Amazon Web Services. At Google, Carl learned from the world’s foremost experts in machine learning and also helped manage the company’s efforts to democratize artificial intelligence. You can learn more about Carl from his blog Clouds With Carl.

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With an emphasis on clarity, style, and performance, author J.T. Wolohan expertly guides you through implementing a functionally-influenced approach to Python coding. You’ll get familiar with Python’s functional built-ins like the functools operator and itertools modules, as well as the toolz library. Mastering Large Datasets teaches you to write easily readable, easily scalable Python code that can efficiently process large volumes of structured and unstructured data. By the end of this comprehensive guide, you’ll have a solid grasp on the tools and methods that will take your code beyond the laptop and your data science career to the next level!Key features• An introduction to functional and parallel programming • Data science workflow • Profiling code for better performance • Fulfilling different quality objectives for a single unifying task • Python multiprocessing • Practical exercises including full-scale distributed applicationsAudienceReaders should have intermediate Python programming skills.About the technologyPython is a data scientist’s dream-come-true, thanks to readily available libraries that support tasks like data analysis, machine learning, visualization, and numerical computing. J.T. Wolohan is a lead data scientist at Booz Allen Hamilton and a PhD researcher at Indiana University, Bloomington, affiliated with the Department of Information and Library Science and the School of Informatics and Computing. His professional work focuses on rapid prototyping and scalable AI. His research focuses on computational analysis of social uses of language online.

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There’s a lot more to the blockchain than mining Bitcoin. This secure system for registering and verifying ownership and identity is perfect for supply chain logistics, health records, and other sensitive data management tasks. Blockchain in Action unlocks the full potential of this revolutionary technology, showing you how to build own decentralized apps for secure applications including digital democracy, private auctions, and electronic record management. Key Features · How blockchain differs from other distributed systems · Smart contract development with Ethereum and the Solidity language · Web UI for decentralized apps · Identity, privacy and security techniques · On-chain and off-chain data storage For intermediate programmers who know the basics of object-oriented languages and have a working knowledge of JavaScript. About the technology A blockchain is a decentralized record, stored across numerous devices with no central control or authority. Copies of this shared database are constantly reconciled with one another, and records are cryptographically encoded to make them unchangeable. The result is a type of database that is at once transparent and publicly accessible, and where it is impossible to falsify or alter the historic data record. Bina Ramamurthy holds a Ph.D. in fault-tolerant distributed systems, and has thirty years of experience teaching cryptography, peer-to-peer networking, and distributed systems. She is the instructor and content creator for the University of Buffalo four-course specialization on blockchain technology on the Coursera MOOC platform, and the recipient of the 2019 SUNY Chancellor’s Award for Teaching Excellence.

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Imagine predicting which customers are thinking about switching to a competitor or flagging potential process failures before they happen Think about the benefits of automating tedious business processes and back-office tasks Consider the competitive advantage of making decisions when you know the most likely future events Machine learning can deliver these and other advantages to your business, and it’s never been easier to get started! Machine Learning for Business teaches you how to make your company more automated, productive, and competitive by mastering practical, implementable machine learning techniques and tools. Thanks to the authors’ down-to-earth style, you’ll easily grok why process automation is so important and why machine learning is key to its success. In this hands-on guide, you’ll work through seven end-to-end automation scenarios covering business processes in accounts payable, billing, payroll, customer support, and other common tasks. Using Amazon SageMaker (no installation required!), you’ll build and deploy machine learning applications as you practice takeaway skills you’ll use over and over. By the time you’re finished, you’ll confidently identify machine learning opportunities in your company and implement automated applications that can sharpen your competitive edge! Key Features Identifying processes suited to machine learning Using machine learning to automate back office processes Seven everyday business process projects Using open source and cloud-based tools Case studies for machine learning decision making For technically-inclined business professionals or business developers. No previous experience with automation tools or programming is necessary. Doug Hudgeon runs a business automation consultancy, putting his considerable experience helping companies set up automation and machine learning teams to good use. In 2000, Doug launched one of Australia’s first electronic invoicing automation companies. Richard Nichol has over 20 years of experience as a data scientist and software engineer. He currently specializes in maximizing the value of data through AI and machine learning techniques.

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Description The Redux JavaScript library consolidates state in a single object, radically simplifying one of the largest sources of bugs. With Redux in Action, you'll discover how to integrate Redux into your React application and development environment, write custom middleware, and optimize for performance. Key features · Clear introduction · Hands-on examples · Step-by-step guide Audience Written for web developers comfortable with JavaScript and ES6, as well as experience using React. About the technology Whether users are passing data through several layers of components or sharing and syncing data between unrelated parts of the app, Redux makes state management a breeze. Redux promotes predictability, testability, and the ability to debug dynamic applications, letting users focus on building great apps. Author biography Marc Garreau has architected and executed half a dozen unique client-side applications leveraging Redux for state management. Will Faurot is experienced in equal parts production Redux, and mentoring Redux developers of all skill levels.

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Description Microservices break down a large application into smaller components, each interacting with each other to create a united whole. As each component can start, stop, and scale independently, so the whole system benefits from better fault-tolerance and resilience. Enterprise Java Microservices is an example-rich tutorial that shows readers how to design and manage large-scale Java applications as a collection of microservices. Key features · The microservices mental model · Fault tolerance with Netflix Hystrix · Securing your microservices · Deploying to the cloud Audience This book is for Java developers familiar with distributed n-tier application architecture. About the technology Enterprise Java is a set of APIs, and their implementations, that can provide the entire stack of an application from UI down to the database, communicate with external applications via webservices, and integrate with internal legacy systems, to name a few, with the goal of supporting the business requirements of an Enterprise. Ken Finnigan has worked as an engineer and consultant for nearly 20 years. He currently co-leads the development of WildFly Swarm for Red Hat.

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Unlike any other programming language, Haskell is purely functionalwith a strong type system and lazy evaluation. It is arguable the mostinteresting language but also has the reputation of being one of themost challenging to learn. Learning Haskell doesn't have to bedifficult, and this book can help! Get Programming with Haskell introduces you to the Haskell languagewithout drowning you in academic jargon and heavy functionalprogramming theory. By working through 43 easy-to-follow lessons,you'll learn Haskell by doing Haskell. This book starts with firstconcepts, building your knowledge with concrete examples andexercises. You'll learn to think the Haskell way, as you start tounderstand the language and how to use it effectively. And you'll reallyappreciate the crystal-clear illustrations, quick-checks, and open-endedtasks that make sure you're solid on each new concept before you movealong! KEY FEATURES• Full of interesting examples• Easy approach to functional programming basics• Write safe, predictable code with fewer bugs• Lots of illustrations and exercises Readers should have some experience with JavaScript, Python orRuby. No functional programming or math skills required. ABOUT THE TECHNOLOGYHaskell is a purely functional programming language. It treats programs asmuch like math as you can, requires you to think more than you type, andcan express the idea of infinite lists in code! These are just the more obviousfeatures that make Haskell unlike any other programming language AUTHOR BIOWill Kurt currently works as a Data Scientist at Quick Sprout. With aformal background in both Computer Science (MS) and English Literature(BA) he is fascinated with explaining complex technical topics as clearlyand generally as possible. He has taught a course section on Haskell at theUniversity of Nevada, Reno and given workshops on FunctionalProgramming. He also blogs about probability at CountBayesie.com.

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