Search results for ""author manny"

Running your systems in the cloud doesn't automatically make them secure. To create secure applications and infrastructure on AWS, you need to understand the tools and features the platform provides and learn new approaches to configuring and managing them. Written by security engineer Dylan Shields, AWS Security provides comprehensive coverage on the key tools and concepts you can use to defend AWS-based systems. You'll learn how to honestly assess your existing security protocols, protect against the most common attacks on cloud applications, and apply best practices to configuring Identity and Access Management and Virtual Private Clouds. about the technology Rapid iteration, easy scaling, and huge savings have caused a mass migration to AWS. However, running in the cloud requires you to modify the security practices you use in on-prem infrastructure. Users of AWS who fail to adapt run the risk of exposing their business and their customers to an attack. Luckily, AWS comes with a stack of tools and services that offer a high level of control over your cloud security. about the book AWS Security is an invaluable guide that you'll want to have on hand when you're facing any cloud security problem. With a cookbook-style delivery, it's filled with well-documented examples and procedures you can apply to common AWS security issues. This book covers best practices for access policies, data protection, auditing, continuous monitoring, and incident response. You'll also explore several deliberately insecure applications, including a social media site and a mobile app, learning the exploits and vulnerabilities commonly used to attack them and the security practices to counter those attacks. With this practical primer, you'll be well prepared to evaluate your system's security, detect threats, and respond with confidence. what's inside Securely grant access to AWS resources to coworkers and customers Develop policies for ensuring proper access controls Lock-down network controls using VPCs Record audit logs and use them to identify attacks Track and assess the security of an AWS account Common attacks and vulnerabilities about the reader For software and security engineers building and securing AWS applications. about the author Dylan Shields is a software engineer working on Quantum Computing at AWS. Previously, Dylan was the first engineer on the AWS Security Hub team. He has also worked at Google Cloud, focusing on the security and reliability of their serverless data warehouse, BigQuery.

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Complex calculations, like training deep learning models or running large-scale simulations, can take an extremely long time. Efficient parallel programming can save hours—or even days—of computing time. Parallel and High Performance Computing shows you how to deliver faster run-times, greater scalability, and increased energy efficiency to your programs by mastering parallel techniques for multicore processor and GPU hardware. about the technologyModern computing hardware comes equipped with multicore CPUs and GPUs that can process numerous instruction sets simultaneously. Parallel computing takes advantage of this now-standard computer architecture to execute multiple operations at the same time, offering the potential for applications that run faster, are more energy efficient, and can be scaled to tackle problems that demand large computational capabilities. But to get these benefits, you must change the way you design and write software. Taking advantage of the tools, algorithms, and design patterns created specifically for parallel processing is essential to creating top performing applications. about the book Parallel and High Performance Computing is an irreplaceable guide for anyone who needs to maximize application performance and reduce execution time. Parallel computing experts Robert Robey and Yuliana Zamora take a fundamental approach to parallel programming, providing novice practitioners the skills needed to tackle any high-performance computing project with modern CPU and GPU hardware. Get under the hood of parallel computing architecture and learn to evaluate hardware performance, scale up your resources to tackle larger problem sizes, and deliver a level of energy efficiency that makes high performance possible on hand-held devices. When you’re done, you’ll be able to build parallel programs that are reliable, robust, and require minimal code maintenance. This book is unique in its breadth, with discussions of parallel algorithms, techniques to successfully develop parallel programs, and wide coverage of the most effective languages for the CPU and GPU. The programming paradigms include MPI, OpenMP threading, and vectorization for the CPU. For the GPU, the book covers OpenMP and OpenACC directive-based approaches and the native-based CUDA and OpenCL languages. what's inside Steps for planning a new parallel project Choosing the right data structures and algorithms Addressing underperforming kernels and loops The differences in CPU and GPU architecture about the readerFor experienced programmers with proficiency in a high performance computing language such as C, C++, or Fortran. about the authors Robert Robey has been active in the field of parallel computing for over 30 years. He works at Los Alamos National Laboratory, and has previously worked at the University of New Mexico, where he started up the Albuquerque High Performance Computing Center. Yuliana Zamora has lectured on efficient programming of modern hardware at national conferences, based on her work developing applications running on tens of thousands of processing cores and the latest GPU architectures.

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Build a microservices application from scratch using industry standard tools and battle-tested best practices.The best way to learn microservices development is to build something! Bootstrapping Microservices with Docker, Kubernetes, GitHub Actions, and Terraform, Second Edition guides you from zero through to a complete microservices project, including fast prototyping, development, and deployment. In Bootstrapping Microservices, Second Edition you’ll get hands-on experience with microservices development skills like: Creating, configuring, and running a microservice with Node.js Building and publishing a microservice using Docker Applying automated testing Running a microservices application in development with Docker Compose Deploying microservices to a production Kubernetes cluster Implementing infrastructure as code and setting up a continuous delivery pipeline Monito

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The Art of Unit Testing, Third Edition updates an international bestseller to reflect modern development tools and practices. This expanded edition teaches you to write unit tests for async and observable code, as well as methods of faking functions, modules and refactorings. You'll explore test patterns and organization, working with legacy code, and even "untestable" code. The many tool-agnostic examples are presented in JavaScript, and are carefully designed so that they apply to code written in any language. about the technology Unit testing is a universally-adopted practice on dev teams of all sizes. Great developers will tell you that testing is as much a state of mind as a collection of tools and practices. The Art of Unit Testing, Third Edition takes you below the surface and understand how unit testing can transform the way you deliver and maintain software. Now with examples in JavaScript, this new edition has been updated to reflect the characteristics of a modern codebase, including async and modularized, distributed services. The practices and patterns you'll learn can also be easily applied to other languages, including C#, Java, and Python. about the book The Art of Unit Testing, Third Edition guides you step by step from your first simple unit tests to building complete test sets that are maintainable, readable, and trustworthy. Now with examples using JavaScript and Node, this expanded third edition teaches you to write unit tests for async and observable code, as well as methods of faking functions, modules and refactorings. You'll get to grips with complex subjects such as mocks and stubs, explore how to handle tricky legacy codebases, and save yourself time with tests that function for both frontend and backend applications. The Art of Unit Testing, Third Edition is an essential guide for any unit tester who wants to feel confident writing code that's easier to create, maintain, and adapt.

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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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　 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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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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This revision of Manning's popular The Quick Python Book offers a clear, crisp introduction to the elegant Python programming language and its famously easy-to-read syntax. After exploring Python's syntax, control flow, and basic data structures, the book shows how to create, test, and deploy full applications and larger code libraries. It addresses established Python features as well as the advanced object-oriented options available in Python 3. This edition covers 5 years’ worth of minor updates to the language, and the last 5 chapters have been reworked to be data based project work. Key features: · Clear introduction · Completely up-to-date · Hands-on experience The book is aimed at readers who know programming but for whom the Python language is new. About the Technology: Python is a true cross-platform language. It can be used to develop small applications and rapid prototypes, but scales well to permit development of large programs. It comes with a powerful and easy-to-use graphical user interface (GUI) toolkit, web programming libraries and more. And it’s free!

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DESCRIPTION In a world where big data is the norm and near-real-time decisions are crucial, machine learning (ML) is a critical component of the data workflow. Machine learning systems can quickly crunch massive amounts of information to offer insights and make decisions in a way that matches or even surpasses human cognitive abilities. These systems use sophisticated computational and statistical tools to build models that can recognize and visualize patterns, predict outcomes, forecast values, and make recommendations. Real-World Machine Learning is a practical guide designed to teach developers the art of ML project execution. The book introduces the day-to-day practice of machine learning and prepares readers to successfully build and deploy powerful ML systems. Using the Python language and the R statistical package, it starts with core concepts like data acquisition and modeling, classification, and regression. Then it moves through the most important ML tasks, like model validation, optimization and feature engineering. It uses real-world examples that help readers anticipate and overcome common pitfalls. Along the way, they will discover scalable and online algorithms for large and streaming data sets. Advanced readers will appreciate the in-depth discussion of enhanced ML systems through advanced data exploration and pre-processing methods. KEY FEATURES Accessible and practical introduction to machine learning Contains big-picture ideas and real-world examples Prepares reader to build and deploy powerful predictive systems Offers tips & tricks and highlights common pitfalls AUDIENCE Code examples are in Python and R. No prior machine learning experience required. ABOUT THE TECHNOLOGY Machine learning has gained prominence due to the overwhelming successes of Google, Microsoft, Amazon, LinkedIn, Facebook, and others in their use of ML. The Gartner report predicts that big data analytics will be a $25 billion market by 2017, and financial firms, marketing organizations, scientific facilities, and Silicon Valley startups are all demanding machine learning skills from their developers.

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DESCRIPTION Whether handling big data, building cloud-based services, or developing multi-tenant web applications, it's vital to have a fast, reliable search solution. Apache Solr is a scalable and ready-to-deploy open-source full-text search engine powered by Lucene. It offers key features like multi-lingual keyword searching, faceted search, intelligent matching, and relevancy weighting right out of the box. Solr in Action is the definitive guide to implementing fast and scalable search using Apache Solr 4. It uses well-documented examples ranging from basic keyword searching to scaling a system for billions of documents and queries. Readers will gain a deep understanding of how to implement core Solr capabilities such as faceted navigation through search results, matched snippet highlighting, field collapsing and search results grouping, spell checking, query auto-complete, querying by functions, and more. RETAIL SELLING POINTS Clearly-written comprehensive guide In-depth coverage of Solr 4 Uses real-world examples backed by years of experience AUDIENCE This book assumes some knowledge of Java and standard database technology. No prior experience with Solr or Lucene is required. ABOUT THE TECHNOLOGY Solr 4 provides new features to enable large-scale distributed search solutions that can be deployed as an elastically scaling cloud-based service and can provide additional intelligence to other big data technologies like Hadoop and Mahout.

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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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DESCRIPTION Node.js has rapidly become a viable choice for large-scale web applications that previously relied on Java, PHP, or Rails. Sails.js is a modern MVC framework for Node that radically simplifies back-end web development. Sails provides full support for data access, real-time programming with web sockets, enterprise-caliber security, and modern development workflow patterns. It also offers powerful productivity features like rapid API development via Sails blueprints, task automation via node-machines, and easy integration with frontend frameworks like Ember and Angular. Sails.js in Action is a comprehensive guide to building enterprisecapable web applications using Node and Sails. Written by the creators of the Sails.js framework, this book carefully introduces each concept, technique, and tool with real-world examples and crystal-clear explanations. Readers follow perfectly-paced, gap-free instruction as they learn to build the back end of a typical Single Page Web Application. As readers hone skills, they explore advanced features like services, hooks, and file uploads. Along the way, they learn to fully understand Node's asynchronous programming model and the syntax and conventions used to implement it. KEY FEATURES• Real-world examples and crystal-clear explanations • Comprehensive guide to building enterprise level web apps • Learn to build Single Page Web Applications • Teaches concepts and practical techniques AUDIENCE Readers should be comfortable with JavaScript and front-end web development. Perfect for back-end developers making the transition to JavaScript and Node. ABOUT THE TECHNOLOGY Sails.js is a modern MVC framework for Node that radically simplifies back-end web development. Node.js has rapidly become a viable choice for large-scale web applications that previously relied on Java, PHP, or Rails.

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Description Dependency Injection has become one of the most dominant practices in the past decade, and it's now required knowledge for .NET developers. Dependency Injection in .NET, Second Edition teaches readers to use Dependency Injection to reduce hard-coded dependencies between application components. Readers will dive into thoroughly-explained examples and develop a foundation they can apply to any of the many DI libraries for .NET and .NET Core. Key Features · Integration with common .NET application frameworks · DI patterns and anti-patterns · Aspect-oriented programming · Using Microsoft and open source DI libraries and containers Audience This book is written for intermediate .NET developers and beyond. No previous experience with DI or DI frameworks is required. About the Technology Dependency Injection is an application design pattern where components are loosely-coupled with the objects or data on which they have a dependency.

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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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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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ADO.NET, Microsoft's new data access technology, provides all the standard data access capabilities you would expect. It also solves the unique problems associated with disconnected database access needed for robust n-tier and web applications. ADO.NET Programming covers database programming in .NET and illustrates important steps with nice examples. It shows you how you can achieve effortless separation of data presentation from data access; how to easily go from relational data to XML, and back; how to bind data directly to the Web and Windows Controls; how to write generic access code that talks to multiple databases without change; and much more. Along the way, it illuminates with well-focused examples, points out the gotchas, and teaches best practices. What's inside: Examples in SQL Server, Oracle and MS Access Disconnected data with the DataSet Moving between relational data and XML Binding data to Window an

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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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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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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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Windows or Mac OS X users are often daunted by the Linux operating system. And yet learning Linux doesn't have to be hard and the payoff is great. Linux is secure, flexible, and free. It’s less susceptible to malicious attacks, and when it is, patches are available quickly. And best of all, Linux allows users access to different desktop interfaces and loads of software, almost all of it completely free. Learn Linux in a Month of Lunches shows readers how to install and use Linux for all the things they need to do, like connecting to a network, installing software, and securing your system. Written for readers who are curious about Linux or have to get up and running for a job. This book concentrates on the tasks Linux users need to know how to do. In easy-to-follow lessons designed to take an hour or less, readers learn how to use the command line, along with practical topics like installing software, customizing your desktop, printing, and even basic networking. Readers will find a road map to the commands and processes they need to be instantly productive. Key Features: • Go from Linux novice to expert in just one month • Short, easy-to-follow lessons • Teaches the must-know commands and processes • Covers the most useful Linux topics AUDIENCE This book is for anyone looking to learn how to use Linux ABOUT THE TECHNOLOGY Linux is a free, popular, widely supported, open-source operating system based on UNIX.

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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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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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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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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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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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Functional programming is a way of thinking about programs that emphasizes functions, while avoiding state mutation. C# includes a number of functional features and libraries, enabling us to take advantage of these benefits. Functional Programming in C# teaches readers to apply functional thinking to real-world scenarios. They’ll start by learning the principles of functional programming, and how they translate in the C# language. By the end of this book, readers will be able to integrate functional techniques, making their C# programs robust and maintainable, and helping them to become more well rounded developers. Key Features: · Introduction to functional programming · Real-world examples · Integrate functional techniques · Become a well rounded developer This book is designed to help C# programmers with an OOP background understand functional thinking. About the Technology: Functional programming is a way of thinking about programs that emphasizes functions, while avoiding state mutation. It allows us to write elegant, intention-revealing code, that shines in testability and support for concurrency.

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DESCRIPTION Data accumulated about customers, products, and website users can not only help interpret the past, it can help predict the future! Probabilistic programming is a programming paradigm in which code models are used to draw probabilistic inferences from data. By applying specialized algorithms, programs assign degrees of probability to conclusions and make it possible to forecast future events like sales trends, computer system failures, experimental outcomes, and other critical concerns. Practical Probabilistic Programming explains how to use the PP paradigm to model application domains and express those probabilistic models in code. It shows how to use the Figaro language to build a spam filter and apply Bayesian and Markov networks to diagnose computer system data problems and recover digital images. Then it dives into the world of probabilistic inference, where algorithms help turn the extended prediction of social media usage into a science. The book covers functional-style programming for text analysis and using object-oriented models to predict social phenomena like the spread of tweets, and using open universe models to model real-life social media usage. It also teaches the principles of algorithms such as belief propagation and Markov chain Monte Carlo. The book closes out with modeling dynamic systems by using a product cycle as its main example and explains how probabilistic KEY SELLING POINTS Covers the basic rules of probabilistic inference Illustrated with useful practical examples Build a wide variety of probabilistic models AUDIENCE Code examples are written in Figaro. Some knowledge of Scala and a basic foundation in data science is helpful. No prior exposure to probabilistic programming is required. ABOUT THE TECHNOLOGY Probabilistic programming is a new discipline, and the tools and best practices are still emerging. Powerful new tools like the Figaro library built into Scala make probabilistic programming more practical in day-to-day work as a data scientist.

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DESCRIPTION Any large application needs an efficient way to handle the constant messages passing between components in the system. Billed as "messaging that just works," the RabbitMQ message broker initially appeals to developers because it's lightweight, easy to set up, and low maintenance. They stick with it because it's powerful, fast, and up to nearly anything that can be thrown at it. This book takes readers beyond the basics and explores the challenges of clustering and distributing messages across enterprise-level data-centers using RabbitMQ. RabbitMQ in Depth is a practical guide to building and maintaining message-based systems. This book covers detailed architectural and operational use of RabbitMQ with an emphasis on not just how it works but why it works the way it does. It provides examples and detailed explanations of everything from low-level communication to integration with third-party systems. It also offers insights needed to make core architectural choices and develop procedures for effective operational management. KEY FEATURES Approachable detailed resource Explains the "how" and "why" of RabbitMQ Takes readers well beyond the basics AUDIENCE Written for programmers with a basic understanding of messaging oriented systems and RabbitMQ. ABOUT THE TECHNOLOGY RabbitMQ is an open-source message broker software that programs can use to exchange messages with each other to create scalable and reliable application architectures.

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Learn Anthos directly from the Google development team! Anthos delivers a consistent management platform for deploying and operating Linux and Windows applications anywhere—multicloud, edge, on-prem, bare metal, or VMware. In Google Anthos in Action you will learn: How Anthos reduces your dependencies and stack-bloat Running applications across multiple clouds and platforms Handling different workloads and data Adding automation to speed up code delivery Modernizing infrastructure with microservices and Service Mesh Policy management for enterprises Security and observability at scale In a cloud-centric world, all deployment is becoming hybrid deployment. Anthos is a modern, Kubernetes-based cloud platform that enables you to run your software in multicloud, hybrid, or on-premises deployments using the same operations tools and approach. With powerful automation features, it boosts your efficiency along the whole development lifecycle. Google Anthos in Action demystifies Anthos with practical examples of Anthos at work and invaluable insights from the Google team that built it. about the technology Anthos is built on a simple concept: write once, and run anywhere—whether that's on-prem, in any public cloud, on the edge, or all three. As the first truly multicloud platform from a major provider, Anthos was designed with the practical goals of balancing cost, efficiency, security, and performance. Anthos lets you simplify your stack, deliver software faster with cloud-native tooling, and automatically integrate high levels of security into your deployments. about the book Google Anthos in Action comes directly from the Anthos team at Google. This comprehensive book takes a true DevOps mindset, considering Google-tested patterns for how an application is designed, built, deployed, managed, monitored, and scaled. Developers will love how having a consistent platform across clouds brings a massive performance boost by standardizing the application across deployment targets, as well as how Anthos makes it easy to modernize legacy applications to cloud native infrastructure. Operations pros will appreciate how simple it is to integrate Anthos with CI/CD pipelines, automate security and policy management, and work with enterprise-level Kubernetes. Each concept is fully illustrated with exercises and hands-on examples, so you can see the power of Anthos in action. RETAIL SELLING POINTS • How Anthos reduces your dependencies and stack-bloat • Running applications across multiple clouds and platforms • Handling different workloads and data • Adding automation to speed up code delivery • Modernizing infrastructure with microservices and Service Mesh • Policy management for enterprises • Security and observability at scale AUDIENCE For software and cloud engineers with knowledge of Kubernetes.

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Create fully featured APIs with the ASP.NET Core framework! Building Web APIs with ASP.NET Core is a practical beginner's guide to creating your first web APIs using the REST and GraphQL standards. The book is structured just like a real-world development project, with each chapter introducing a new feature request. This edition will help you develop an API that feeds web-based services, including websites and mobile apps, for a board games application. You will build your API with an ecosystem of ASP.NET Core tools that helps simplify everything from setting up your data model to generating documentation. You will learn how to: Set up your environment with VS 2022, Node, Git, and more Create an ASP.NET Core project from scratch Integrate with SQL Server Use Entity Framework Core to set up a data model Create back-end controllers Design an API to serve data Write API documentation using Swagger and Swashbuckle Consume an API using typical web client-side frameworks, including Angular and ReactJS Handle requests and routes using controllers and Minimal API About the technology APIs are the backbone of modern software and a vital skill for anyone serious about professional development. The free and open-source ASP.NET Core framework is one of the best tools available for creating APIs! It is designed to maximise code execution speed and reliability, and its “no compile” development experience means you are never stuck waiting for your code. Widely used by both small companies and big enterprises, ASP.NET Core benefits from both the support of its open-source community and the backing of Microsoft and the Azure cloud.

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A friendly, fully-illustrated introduction to the most important computer programming algorithms. The algorithms you''ll use most often as a programmer have already been discovered, tested, and proven. This book will prepare you for those pesky algorithms questions in every programming job interview and help you apply them in your day-to-day work. And if you want to understand them without slogging through dense multipage proofs, this is the book for you. In Grokking Algorithms, Second Edition you will discover: Search, sort, and graph algorithms Data structures such as arrays, lists, hash tables, trees, and graphs NP complete and greedy algorithms Performance trade-offs between algorithms Exercises and code samples in every chapter Over 400 illustrations with detailed walkthroughs The first edition of Grokking Algorithms proved to over 100,000 readers that learning algorithm

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Build professional-grade full-stack web applications using C# and ASP.NET Core. ASP.NET Core in Action, 3rd edition by Microsoft MVP Andrew Lock, is a fully updated edition, ideal for intermediate C# developers, and teaches you how to use your C# and .NET skills to build amazing cross-platform web applications. This revised bestseller reveals the latest .NET patterns, including minimal APIs and minimal hosting. Even if you have never worked with ASP.NET, you will soon start creating productive cross-platform web apps. Features include: Build minimal APIs for serving JSON to client-side applications Create dynamic, server-side rendered applications using Razor Pages User authentication and authorisation Store data using Entity Framework Core Unit and integration tests for ASP.NET Core applications Write custom middleware and components About the technology Developers love ASP.NET Core for its libraries and pre-built components that maximize productivity. This awesome web framework empowers you to build web applications using HTTP APIs, server-side rendered HTML, and long-running server processes - all by using the same familiar structure and components. Version 7.0 takes full advantage of new C# features, easy-to-build minimal APIs, and big performance upgrades.

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Take PowerShell beyond simple scripts and build time-saving automations for your team, your users, and the world. In Practical Automation with PowerShell you will learn how to: Build PowerShell functions to automate common and complex tasks Create smart automations that are adaptable to new challenges Structure your code for sharing and reusability Store and secure your automations Execute automations with Azure Automation, Azure Functions, and Jenkins Share your automations with your team and non-technical colleagues Store and retrieve data, credentials, and variables Use source control solutions to maintain and test code changes Provide front-end UI solutions for PowerShell automations Practical Automation in PowerShell reveals how you can use PowerShell to build automation solutions for a huge number of common admin and DevOps tasks. It takes you beyond scripting basics and shows you how to handle the unforeseen complexities that can keep automations from becoming reusable and resilient. You'll discover tools and platforms that let you share your automations with your team and even roll them out to non-technical users through easy-to-understand Sharepoint frontends. about the technology Most repetitive tasks you face as an administrator or DevOps engineer can be automated using PowerShell. Mastering the basics of this powerful language, along with some best practices for saving and sharing your automations, can radically improve the consistency and efficiency of your work. about the book Practical Automation with PowerShell teaches you how to build, organize, and share useful automations with PowerShell. You'll start with development skills you might not have learned as a sysadmin, including techniques to help you structure and manage your code, and common pitfalls to avoid. You'll quickly progress to essential factors for sharable automations, such as securely storing information, connecting to remote machines, and creating automations that can adapt to different use cases. Finally, you'll take your automations out into the world. You'll learn how to share them with your team or end users, and build front ends that allow non-technical people to run them at the touch of a button.

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Discover one-of-a-kind AI strategies never before seen outside of academic papers! Learn how the principles of evolutionary computation overcome deep learning's common pitfalls and deliver adaptable model upgrades without constant manual adjustment. In Evolutionary Deep Learning you will learn how to: Solve complex design and analysis problems with evolutionary computation Tune deep learning hyperparameters with evolutionary computation (EC), genetic algorithms, and particle swarm optimization Use unsupervised learning with a deep learning autoencoder to regenerate sample data Understand the basics of reinforcement learning and the Q Learning equation Apply Q Learning to deep learning to produce deep reinforcement learning Optimize the loss function and network architecture of unsupervised autoencoders Make an evolutionary agent that can play an OpenAI Gym game Evolutionary Deep Learning is a guide to improving your deep learning models with AutoML enhancements based on the principles of biological evolution. This exciting new approach utilizes lesser-known AI approaches to boost performance without hours of data annotation or model hyperparameter tuning. about the technology Evolutionary deep learning merges the biology-simulating practices of evolutionary computation (EC) with the neural networks of deep learning. This unique approach can automate entire DL systems and help uncover new strategies and architectures. It gives new and aspiring AI engineers a set of optimization tools that can reliably improve output without demanding an endless churn of new data. about the reader For data scientists who know Python.

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It's time to dispel the myth that machine learning is difficult. Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math. No specialist knowledge is required to tackle the hands-on exercises using readily available machine learning tools! In Grokking Machine Learning, expert machine learning engineer Luis Serrano introduces the most valuable ML techniques and teaches you how to make them work for you. Practical examples illustrate each new concept to ensure you’re grokking as you go. You’ll build models for spam detection, language analysis, and image recognition as you lock in each carefully-selected skill. Packed with easy-to-follow Python-based exercises and mini-projects, this book sets you on the path to becoming a machine learning expert. Key Features · Different types of machine learning, including supervised and unsupervised learning · Algorithms for simplifying, classifying, and splitting data · Machine learning packages and tools · Hands-on exercises with fully-explained Python code samples For readers with intermediate programming knowledge in Python or a similar language. About the technology Machine learning is a collection of mathematically-based techniques and algorithms that enable computers to identify patterns and generate predictions from data. This revolutionary data analysis approach is behind everything from recommendation systems to self-driving cars, and is transforming industries from finance to art. Luis G. Serrano has worked as the Head of Content for Artificial Intelligence at Udacity and as a Machine Learning Engineer at Google, where he worked on the YouTube recommendations system. He holds a PhD in mathematics from the University of Michigan, a Bachelor and Masters from the University of Waterloo, and worked as a postdoctoral researcher at the University of Quebec at Montreal. He shares his machine learning expertise on a YouTube channel with over 2 million views and 35 thousand subscribers, and is a frequent speaker at artificial intelligence and data science conferences.

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Turn the corner from “Haskell student” to “Haskell developer.” Haskell in Depth explores the important language features and programming skills you’ll need to build production-quality software using Haskell. And along the way, you’ll pick up some interesting insights into why Haskell looks and works the way it does. Get ready to go deep! Haskell in Depth is the perfect second book on Haskell. After a quick refresher on Haskell basics, this hands-on guide dives into examples and application scenarios designed to teach how Haskell works and how to apply it correctly. You’ll learn about managing projects with Cabal and Stack, tackle error-handling and testing, and package programs and libraries for production deployment. Key Features · Organizing your projects with Cabal and Stack · Testing and profiling · Working with data · Building web services and networking apps · Using the sophisticated libraries like lens, vinyl, and servant Written for developers familiar with Haskell basics. About the technology As software becomes more complex, it’s essential to program efficiently using tools and techniques that guarantee your applications will run correctly, grow easily, and last a long time. Haskell is a functional programming language that blends a mathematically-rigorous approach to software design with a tested ecosystem of tools and libraries you can use to build deployable applications. Since 2008, Vitaly Bragilevsky has been teaching Haskell and functional programming to undergraduate students at the Southern Federal University located in Rostov-on-Don, Russia. He is a member of the Haskell 2020 Committee, and has worked on the source code of the Glasgow Haskell Compiler (GHC) and the Idris compiler, both of which are implemented in Haskell.

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