Search results for """ "Modern HTML CSS with AI""

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Book SynopsisGet to grips with the LangChain framework from theory to deployment and develop production-ready applications. Code examples regularly updated on GitHub to keep you abreast of the latest LangChain developments. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Learn how to leverage LLMs’ capabilities and work around their inherent weaknesses Delve into the realm of LLMs with LangChain and go on an in-depth exploration of their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Bard. It also demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Understand LLMs, their strengths and limitations Grasp generative AI fundamentals and industry trends Create LLM apps with LangChain like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is forThe book is for developers, researchers, and anyone interested in learning more about LLMs. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs and are looking to stay ahead of the curve in the LLMs and LangChain arena. Basic knowledge of Python is a prerequisite, while some prior exposure to machine learning will help you follow along more easily.Table of ContentsTable of Contents What Is Generative AI? LangChain for LLM Apps Getting Started with LangChain Building Capable Assistants Building a Chatbot like ChatGPT Developing Software with Generative AI LLMs for Data Science Customizing LLMs and Their Output Generative AI in Production The Future of Generative Models

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Book SynopsisProviding an introduction to programming on the Internet, this book covers the basics of Internet programming. In addition to core fundamentals, readers are introduced to web page construction using HTML, managing an account on a web server, client-server model, and JavaScript programming.Trade Review"overall this is a good place to start in HTML & JavaScript." (M2 Communications, 15 March 2001)Table of ContentsThe Internet and World Wide Web. Transactions on the Web. Text Markup. Controlling Text Markup. Hypertext Markup and Web Sites. Image Markup. HTML Lists and Tables. HTML Frames. What is Javascript? Processing User Input. Making Decisions. Objects. Introduction to Processing HTML Forms. Options in HTML Forms. Loops for Repetition. More on Arrays. More on Functions. Javascript Security and Submitting Form Data. Appendices. Index.

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Book SynopsisHTML es, sin duda, el primer paso para todo aquel que se interese por el diseño de páginas web, de ahí la importancia de este lenguaje para los futuros aspirantes a webmaster, ya que aunque deberán conocer y dominar otras disciplinas, HTML es ABSOLUTAMENTE imprescindible.Este libro pretende ser un método de aprendizaje sencillo y asequible, a la vez que rigurosamente profesional, por ello, comienza desde cero, exponiendo los conceptos más elementales para a su debido tiempo desarrollar las técnicas más avanzadas: el llamado HTML dinámico o DHTML. El lector aprenderá a crear sus propias páginas web, controlando a su gusto el texto, imágenes, tablas, enlaces, colores, marcos, capas, etc., y cuando domine las técnicas expuestas, también le servirá como guía de referencia, ya que aporta una serie de datos adicionales de uso muy común.El autor, como profesional de la enseñanza informática, principalmente de todo lo relacionado con tecnologías web, ha plasmado en la obra la experienc

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Book SynopsisHTML5 Hacks shows you how to use the latest tools to make your sites and applications more interactive, more functional, and more capable of competing with desktop applications. Each hack shows you how to make a concrete improvement, applying the latest in JavaScript, HTML, and CSS power to common web development issues.

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Book Synopsis"Modern Compiler Design" makes the topic of compiler design more accessible by focusing on principles and techniques of wide application.Trade ReviewFrom the reviews of the second edition:“This large, updated new edition … provides excellent coverage of the design segment. The writing is clear and accessible; the material is well organized and complete; the references are extensive (over 300) and the student exercises are well conceived … . the essence of the book is the middle ground between the two: how compilers are structured and how the substructures of a compiler relate to one another. Summing Up: Recommended. Computer science collections, upper-division undergraduates and above.” (C. Vickery, Choice, Vol. 50 (6), February, 2013)Table of ContentsIntroduction.- Program Text to Tokens— Lexical Analysis.- Tokens to Syntax Tree— Syntax Analysis.- Grammar-based Context Handling.- Manual Context Handling.- Interpretation.- Code Generation.- Assemblers, Disassemblers, Linkers, and Loaders.- Optimization Techniques.- Explicit and Implicit Memory Management.- Imperative and Object-Oriented Programs.- Functional Programs.- Logic Programs.- Parallel and Distributed Programs.

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Book SynopsisEstos tres libros ofrecen al lector un máximo de información sobre el lenguaje C#, HTML5, CSS3 y el framework ASP.NET Core para dominar el desarrollo fullstack. 1239 páginas desarrolladas por nuestros expertos. Hay elementos para descarga en . Un libro de la colección Recursos Informáticos HTML5 y CSS 3 - Domine los estándares de creación de sitios web (3 edición) Este libro sobre el lenguaje HTML5 y las hojas de estilos CSS 3, ambos lenguajes fundacionales de la creación de sitios web, está dirigido a desarrolladores que desean tener los conocimientos necesarios para crear y hacer evolucionar sitios web, respetando las buenas prácticas... Un libro de la colección Recursos Informáticos C# 12 y Visual Studio Code - Fundamentos del lenguaje Este libro está dirigido a los programadores que quieren dominar el desarrollo de aplicaciones .NET mediante el lenguaje C#, aquí en su versión 12... Un libro de la colección Expert IT ASP.NET Core MVC - Domine este potente framework web abierto y multiplataforma Este libro se dirige a desarrolladores web que deseen dominar ASP.NET Core MVC, un framework de código completamente abierto ofrecido por Microsoft. El autor desea proporcionar al lector los fundamentos técnicos necesarios para un uso óptimo del framework, para crear aplicaciones web ricas y modernas. El conocimiento de HTML, CSS y C# son requisitos previos esenciales para aprovechar al máximo el libro...

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Book SynopsisOriginally published in 1989 The Industrialization of Intelligence is a critically-acclaimed collection of essays about the political and social impacts of information technology. Table of ContentsAcknowledgements. Introduction: Capital Lost 1. The Machinery of Self-Love 2. Machinery and Labour 3. The Division of Mental Labour 4. The Laws of Thought 5. Origins of a System 6. Of Little Men and Monsters 7. Systems of Belief, Systems of Production 8. Technology and Employment 9. Human Capital and the Wealth of Nations. Epilogue: On Leading the Leading Edge. Notes and References. Bibliography. Index.

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Book SynopsisAlgorithmic Modernity brings together experts in the history of mathematics to create an informed history for readers interested in the social and cultural implications of today's pervasive digital algorithm.Trade ReviewAlgorithms are both centuries old and central to today's hopes and fears. In this compelling book, ten first-rate historians of science and mathematics trace the genealogy of algorithmic practices and ideas that play a crucial role in the modern world. * Donald MacKenzie, University of Edinburgh *Table of ContentsIntroduction Morgan G. Ames and Massimo Mazzotti Chapter 1: Algorithm and Demonstration in the Sixteenth-Century Ars Magna Abram Kaplan Chapter 2: "Some call it Arsmetrike, and some Awgryme": Misprision and Precision in Algorithmic Thinking and Learning in 1543 and Beyond Michael J. Barany Chapter 3: The Orderly Universe: How the Calculus Became an Algorithm Amir Alexander Chapter 4: The Algorithmic Enlightenment J.B. Shank Chapter 5: Capitalism by Algorithm: Numbers for the Innumerate in the 18th and 19th Century Atlantic World Caitlin C. Rosenthal Chapter 6: Material Mathematics: British Algebra as Algorithmic Mathematics Kevin Lambert Chapter 7: "For Computing is Our Duty": Algorithmic Workers, Servants, and Women at the Harvard Observatory Andrew Fiss Chapter 8: Seeds of Control: Sugar Beets, Control Algorithms, and New Deal Data Politics Theodora Dryer Chapter 9: Inference Rituals: Algorithms and the History of Statistics Christopher J. Phillips Chapter 10: Decision Trees, Random Forests, and the Genealogy of the Black Box Matthew L. Jones Index

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Book SynopsisTurn Vim into a full-blown development environment using Vim 8's new features and this sequel to the beloved bestseller Practical Vim. Integrate your editor with tools for building, testing, linting, indexing, and searching your codebase. Discover the future of Vim with Neovim: a fork of Vim that includes a built-in terminal emulator that will transform your workflow. Whether you choose to switch to Neovim or stick with Vim 8, you'll be a better developer. A serious tool for programmers and web developers, no other text editor comes close to Vim for speed and efficiency. Make Vim the centerpiece of a Unix-based IDE as you discover new ways to work with Vim 8 and Neovim in more than 20 hands-on tips. Execute tasks asynchronously, allowing you to continue in Vim while linting, grepping, building a project, or running a test suite. Install plugins to be loaded on startup - or on-demand when you need them - with Vim 8's new package support. Save and restore sessions, enabling you to quit Vim and restart again while preserving your window layout and undo history. Use Neovim as a drop-in replacement for Vim - it supports all of the features Vim 8 offers and more, including an integrated terminal that lets you quickly perform interactive commands. And if you enjoy using tmux and Vim together, you'll love Neovim's terminal emulator, which lets you run an interactive shell in a buffer. The terminal buffers fit naturally with Vim's split windows, and you can use Normal mode commands to scroll, search, copy, and paste. On top of all that: Neovim's terminal buffers are scriptable. With Vim at the core of your development environment, you'll become a faster and more efficient developer. What You Need: You'll need a Unix-based environment and an up-to-date release of Vim (8.0 or newer). For the tips about running a terminal emulator, you'll need to install Neovim.

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Book SynopsisAn incisive and essentialguide to building a complete system for derivative scripting InVolume 2 ofModern Computational Finance Scripting for Derivatives and xVA,quantitative finance expertsand practitioners Drs. Antoine Savine and Jesper Andreasen deliver an indispensable and insightfulroadmap to the interrogation, aggregation, and manipulation of cash-flows in a variety of ways. The book demonstrates how to facilitate portfolio-wide risk assessment andregulatory calculations (like xVA). Complete with a professional scripting library written in modern C++, this stand-alone volumewalks readers through the construction of a comprehensiverisk and valuationtool.Thisessentialbook also offers: Effective strategies for improving scripting libraries, from basic exampleslikesupport for dates and vectorsto advanced improvements, including American Monte Carlo techniques Exploration of the concepts of fuzzy logic and risk sensitivities,includiTrade Review“The Global Financial Crisis resulted in profound changes in quants’ Modus Operandi. This timely three-volume set describes some of the tools necessary to deal with these changes. Individual volumes cover in detail several important topics of interest to anyone who wants to stay au courant with modern developments in financial engineering. While the books are predominantly practically oriented, they strike a fine balance between theoretical and applied considerations. The authors are prominent practitioners and indisputable thought-leaders in the field. I recommend this set enthusiastically to anyone who wishes to understand the current and emerging trends in financial engineering.” - Prof. Alexander Lipton, Founder and CEO, Stronghold Labs; Fellow, Connection Science and Engineering, Massachusetts Institute of Technology Table of ContentsMy Life in Script by Jesper Andreasen xi Part I A Scripting Library in C++ Introduction 3 Chapter 1 Opening Remarks 7 Introduction 7 1.1 Scripting is not only for exotics 12 1.2 Scripting is for cash-flows not payoffs 13 1.3 Simulation models 15 1.4 Pre-processing 17 1.5 Visitors 19 1.6 Modern implementation in C++ 21 1.7 Script templates 22 Chapter 2 Expression Trees 25 2.1 In theory 25 2.2 In code 35 Chapter 3 Visitors 41 3.1 The visitor pattern 41 3.2 The debugger visitor 47 3.3 The variable indexer 50 3.4 Pre-processors 54 3.5 Const visitors 55 3.6 The evaluator 57 3.7 Communicating with models 65 Chapter 4 Putting Scripting Together with a Model 71 4.1 A simplistic Black-Scholes Monte-Carlo simulator 71 4.1.1 Random number generators 71 4.1.2 Simulation models 73 4.1.3 Simulation engines 76 4.2 Connecting the model to the scripting framework 76 Chapter 5 Core Extensions and the “Pays” Keyword 81 5.1 In theory 81 5.2 In code 83 Part II Basic Improvements Introduction 93 Chapter 6 Past Evaluator 95 Chapter 7 Macros 97 Chapter 8 Schedules of Cash-Flows 99 Chapter 9 Support for Dates 105 Chapter 10 Predefined Schedules and Functions 109 Chapter 11 Support for Vectors 113 11.1 Basic functionality 113 11.2 Advanced functionality 115 11.2.1 New node types 116 11.2.2 Support in the parser 116 11.2.3 Processing 117 11.2.4 Evaluation 117 Part III Advanced Improvements Introduction 121 Chapter 12 Linear Products 123 12.1 Interest rates and swaps 123 12.2 Equities, foreign exchange, and commodities 125 12.3 Linear model implementation 126 Chapter 13 Fixed Income Instruments 127 13.1 Delayed payments 127 13.2 Discount factors 128 13.3 The simulated data processor 129 13.4 Indexing 129 13.5 Upgrading “pays” to support delayed payments 131 13.6 Annuities 132 13.7 Forward discount factors 132 13.8 Back to equities 132 13.9 Libor and rate fixings 133 13.10 Scripts for swaps and options 134 Chapter 14 Multiple Underlying Assets 137 14.1 Multiple assets 137 14.2 Multiple currencies 139 Chapter 15 American Monte-Carlo 143 15.1 Least Squares Method 143 15.2 One proxy 147 15.3 Additional regression variables 149 15.4 Feedback and exercise 149 15.5 Multiple exercise and recursion 152 Part IV Fuzzy Logic and Risk Sensitivities Introduction 157 Chapter 16 Risk Sensitivities with Monte-Carlo 161 16.1 Risk instabilities 161 16.2 Two approaches toward a solution 165 16.3 Smoothing for digitals and barriers 166 16.4 Smoothing for scripted transactions 168 Chapter 17 Support for Smoothing 169 Chapter 18 An Automated Smoothing Algorithm 175 18.1 Basic algorithm 176 18.2 Nested and combined conditions 179 18.3 Affected variables 179 18.4 Further optimization 180 Chapter 19 Fuzzy Logic 183 Chapter 20 Condition Domains 189 20.1 Fuzzy evaluation of discrete conditions 189 20.1.1 Condition domains 189 20.1.2 Constant conditions 190 20.1.3 Boolean conditions 191 20.1.4 Binary conditions 193 20.1.5 Discrete conditions 193 20.1.6 Putting it all together 197 20.2 Identification of condition domains 198 20.3 Constant expressions 201 Chapter 21 Limitations 203 21.1 Dead and alive 203 21.2 Non-linear use of fuzzy variables 206 Chapter 22 The Smoothing Factor 209 22.1 Scripting support 209 22.2 Automatic determination 211 Part V Application to xVA Chapter 23 xVA 215 Chapter 24 Branching 219 Chapter 25 Closing Remarks 223 25.1 Script examples 223 25.2 Multi-threading and AAD 228 25.3 Advanced LSM optimizations 229 Appendix A Parsing 231 A.1 Preparing for parsing 231 A.2 Parsing statements 234 A.3 Recursively parsing conditions 238 A.4 Recursively parsing expressions 244 A.5 Performance 252 Bibliography 255 Index 257

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Book SynopsisThis book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive quantities of spatiotemporal visual data that are available at low cost. The book covers important scientific discoveries and findings, with a focus on the latest advances in the field. Presenting a coherent structure, the book logically connects novel mathematical formulations and efficient computational solutions for a range of unsupervised learning tasks, including visual feature matching, learning and classification, object discovery, and semantic segmentation in video. The final part of the book proposes a general strategy for visual learning over several generations of student-teacher neural networks, along with a unique view on the future of unsupervised learning in real-world contexts. Offering a fresh approach to this difficult problem, several efficient, state-of-the-art unsupervised learning algorithms are reviewed in detail, complete with an analysis of their performance on various tasks, datasets, and experimental setups. By highlighting the interconnections between these methods, many seemingly diverse problems are elegantly brought together in a unified way. Serving as an invaluable guide to the computational tools and algorithms required to tackle the exciting challenges in the field, this book is a must-read for graduate students seeking a greater understanding of unsupervised learning, as well as researchers in computer vision, machine learning, robotics, and related disciplines. Table of Contents1. Unsupervised Visual Learning: from Pixels to Seeing.- 2. Unsupervised Learning of Graph and Hypergraph Matching.- 3. Unsupervised Learning of Graph and Hypergraph Clustering.- 4. Feature Selection meets Unsupervised Learning.- 5. Unsupervised Learning of Object Segmentation in Video with Highly Probable Positive Features.- 6. Coupling Appearance and Motion: Unsupervised Clustering for Object Segmentation through Space and Time.- 7. Unsupervised Learning in Space and Time over Several Generations of Teacher and Student Networks.- 8. Unsupervised Learning Towards the Future.

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Book SynopsisConocer los principios del lenguaje de hipertexto con marcas HTML. Conocer la evolución del lenguaje HTML en sus sucesivas versiones. Conocer la sintaxis de este lenguaje. Conocer las etiquetas básicas para la edición de páginas web. Aprender a crear páginas web escribiendo código HTML directamente. Facilitar la compresión de los programas de edición de páginas web como Adobe Dreamweaver. A efectos prácticos este manual se basará en la versión HTML4, vigente a fecha de hoy, pero se hará mención 10

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Book SynopsisUnderstand the guiding principles of clean code and how it applies to modern front-end development, accessibility (a11y), semantics, performance, and the Green Web. Highlighting key topics ranging from the foundations of JavaScript and HTML to popular frameworks like React, this book provides best practices to ensure code and applications are easier, more efficient and cost effective to run. Using a web-based application as an example, you'll begin by cleaning and improving its code base by dividing the JavaScript into smaller, reusable and composable functions without side effects. Then, you'll improve the HTML code base by applying Disability Driven Design patterns, focusing on semantics before moving on to improving the architecture with a functional style (immutable, modular and composable). Because the web today needs to be green with reduced loading time and energy consumption, you'll apply some tips and tricks to improve code performance and see how to best monitor it in a continuous and scalable way. What You'll LearnSee how the JavaScript engine works and memory management. Explore in greater detail key focus areas of accessibility and green computingMake applications easier and more cost-effective to runLook closely at clean and sustainable development using JavaScript and ReactWho This Book Is ForProgrammers, developers, engineers and product managers who are looking at cost-efficient ways to make their applications run more smoothly and efficiently.

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Book SynopsisThis title represents an essential resource for understanding the evolving landscape of AI-augmented pedagogy, examining the transformative effects of generative AI (GenAI) on education through the lens of agile course design and project-based learning.Through a detailed analysis of diverse empirical case studies from eight countries between 2015 and 2024, the authors effectively illustrate the dual impact of GenAI on education, academic integrity and teacher autonomy. They demonstrate how GenAI can enhance personalized STEM education and STREAM (Science, Technology, Reading and Writing, Engineering, Arts and Mathematics) instruction, as well as project-based learning, while simultaneously presenting significant challenges. They provide a nuanced assessment of the opportunities and disruptions introduced by GenAI and offer concrete pedagogical strategies for teaching practitioners.This book serves as a vital reference for scholars in GenAI, educational technology and curriculum and instruction. It also provides practical, ready-to-implement pedagogical approaches for pre-service teachers in higher education and primary and secondary schools.

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Book SynopsisFrom a review of the first edition: Modern Data Science with R is rich with examples and is guided by a strong narrative voice. What's more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics (The American Statistician).Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions.The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to undTrade Review"This text continues to be fantastic! There are a number of courses for which I would require this book and others that I would recommend it as a supplement. I would likely require it for courses focused on computing in R or courses in data science. I would include it as a recommended text in introductory and other statistics courses that used R as the software of choice, where this text could be used as a supplemental resource in how to use R to work with data." (Hunter Glanz Cal Poly San Luis Obispo)"Easy for students to read and relate to the exercises and examples. Many questions and hands-on activities with data sets to practice skills." (Lynn Collen, St. Cloud Stat Univ.)"I used the first edition of this book as the primary text for an intermediate data science course a few years ago and I liked it very much…I think that the technical breadth, writing style, and level of difficulty are very clear strengths. Also, my students and I found the `tidyverse` approach to be particularly well-suited for teaching and learning R…and I love that the MDSR book includes such complete code. Students can program everything they see in the book, and often times there are tips & tricks for them to discover along the way just by studying expert code provided by the authors. This really sets MDSR apart from other books I considered for the course." (Matthew Beckman, Penn State University)"[...] To answer a wide range of modern research questions, this book by Baumer, Kaplan, and Horton features an excellent introduction to data wrangling, visualization, statistical modeling, machine learning, and other advanced statistical applications through the RStudio environment following the tidyverse syntax. [...] Overall, Modern Data Science with R, 2nd edition serves as an excellent introductory resource to help develop techniques to extract, transform, visualize, and learn from datasets through the R environment. It focuses on implementing those techniques in R and does not provide a theoretical background for the discussed methods. The book will be a perfect reference for a broad audience ranging from undergraduates in data science courses to advanced graduate students and professionals from a variety of research fields."-Kohma Arai and Vyacheslav Lyubchich, in Technometrics, July 2022"Overall, I enjoyed reading this book. The authors were very good at creating a complete tool for studying data science. Therefore, I recommend this book, for its content, writing, and organization, to graduate students in data science and statistics. I also recommend the book to professionals who should prepare themselves for the challenges they are going to face in the future with the voluminous and heterogenous amount of data that should be timely analyzed to extract meaningful information to guide action."-Georgios Nikolopoulos, in ISCB News, June 2022"The authors have successfully completed the job of choosing the content with relevant topics and, deciding the extent of knowledge to be delivered, and finally, putting them in an understandable sequence. This is a well-written book and does not cover much theory. .. The book’s second edition contents are updated, expanded, revised, split, rewritten and rearranged compared to the first edition. The key changes are the use of recently developed R packages, .... (and) updated exercises in the chapters ..."-Shalabh,in Journal of the Royal Statistical Society Series A, August 2021"[This book] provides an excellent basis for statisticians who want to dig deeper into, for example, data handling, for computer scientists who aim to strengthen their knowledge of statistical methods as well as for all other researchers who are interested in data science in general. ... Each section is structured as an interplay between R-code and explanatory text for understanding. The division into several stand-alone segments is an advantage, because the reader may easily choose the section she or he is interested in without missing relevant information. A key feature of the book is its focus on different example data sets that are available via R-packages or from URLs that are embedded in the text. These data sets are used to illustrate the methodology presented using R-code. Their availability allows the reader to reproduce the code while working with the book. ... It can be warmly recommended to practical researchers who seek a comprehensive overview of different topics in data science with focus on implementations in R."-Annika Hoyer, in Biometrical Journal, August 2021"This text continues to be fantastic! There are a number of courses for which I would require this book and others that I would recommend it as a supplement. I would likely require it for courses focused on computing in R or courses in data science. I would include it as a recommended text in introductory and other statistics courses that used R as the software of choice, where this text could be used as a supplemental resource in how to use R to work with data." -Hunter Glanz, Cal Poly San Luis Obispo"Easy for students to read and relate to the exercises and examples. Many questions and hands-on activities with data sets to practice skills." -Lynn Collen, St. Cloud Stat University"I used the first edition of this book as the primary text for an intermediate data science course a few years ago and I liked it very much…I think that the technical breadth, writing style, and level of difficulty are very clear strengths. Also, my students and I found the `tidyverse` approach to be particularly well-suited for teaching and learning R…and I love that the MDSR book includes such complete code. Students can program everything they see in the book, and often times there are tips & tricks for them to discover along the way just by studying expert code provided by the authors. This really sets MDSR apart from other books I considered for the course." -Matthew Beckman, Penn State University"The authors have covered almost all aspects of data science, a revolutionary field that marries elements of computational thinking and traditional statistical theory. The book can thus equip the readers with the necessary knowledge and skills to extract data from a variety of sources, restructure observations in a form that allows analysis, store data in efficient databases, and work effectively on massive and complex data sets in order to produce actionable information."- Georgios Nikolopoulos, University of Cyprus, ISCB Book Reviews, June 2022.Table of ContentsI Part I: Introduction to Data Science. 1. Prologue: Why data science? 2. Data visualization. 3. A grammar for graphics. 4. Data wrangling on one table. 5. Data wrangling on multiple tables. 6. Tidy data. 7. Iteration. 8. Data science ethics. II. Part II: Statistics and Modeling. 9. Statistical foundations. 10. Predictive modeling. 11. Supervised learning. 12. Unsupervised learning. 13. Simulation. III Part III: Topics in Data Science. 14. Dynamic and customized data graphics. 15. Database querying using SQL. 16. Database administration. 17. Working with spatial data. 18.Geospatial computations. 19. Text as data. 20. Network science. IV Part IV: Appendices.

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Book SynopsisModernist aesthetics in architecture, art, and product design are familiar to many. In soaring glass structures or minimalist canvases, we recognize a time of vast technological advance which affirmed the power of human beings to reshape their environment and to break, radically, from the conventions or constraints of the past. Less well-known, but no less fascinating, is the distillation of modernism in graphic design. This unprecedented TASCHEN publication, authored by Jens Müller, brings together approximately 6,000 trademarks, focused on the period 1940–1980, to examine how modernist attitudes and imperatives gave birth to corporate identity. Ranging from media outfits to retail giants, airlines to art galleries, the sweeping survey is organized into three design-orientated chapters: Geometric, Effect, and Typographic. Each chapter is then sub-divided into form and style led sections such as alphabet, overlay, dots and squares. Alongside the comprehensive catalog, the book features an introduction from Jens Müller on the history of logos, and an essay by R. Roger Remington on modernism and graphic design. Eight designer profiles and eight instructive case studies are also included, with a detailed look at the life and work of such luminaries as Paul Rand, Yusaku Kamekura, and Anton Stankowski, and at such significant projects as Fiat, The Daiei Inc., and the Mexico Olympic Games of 1968. An unrivaled resource for graphic designers, advertisers, and branding specialists, Logo Modernism is equally fascinating to anyone interested in social, cultural, and corporate history, and in the sheer persuasive power of image and form.Trade Review“This fantastic collection of handsome logos testifies to the enduring power of clean, crisp, universally symbolic design language that is a far cry from the often trendy, cheesy, puffed-up corporate branding that exists today. […] Logo Modernism is a brilliant catalog of what good corporate logo design looks like.” * Slate.com *“…blockbuster new book Logo Modernism…is a beautiful distillation of modernist ideals rendered in their most superbly crafted way.” * Itsnicethat.com *“…This book is not only full-to-bursting with hugely important logos, it is physically huge!… If you have an interest in social, cultural or corporate history, this is an unrivalled resource and deserves a place on your shelves (if it will fit).” * FormFIftyFive.com *“…Almost limitless as a logo archive for the period, TASCHEN’s Logo Modernism means business about the business of good design.” * PedroSilmon.com *

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Book Synopsis The main subjects in this book relate to software development using cutting-edge technologies for real-world industrial automation applications A hands-on approach to applying a wide variety of emerging technologies to modern industrial practice problems Explains key concepts through clear examples, ranging from simple to more complex problem domains, and all based on real-world industrial problems A useful reference book for practicing engineers as well as an updated resource book for researchers Table of ContentsPreface. Acknowledgments. Acroyms. Part I. Design Principles of Modern Industrial Automation Systems. 1. Introduction. 2. Virtual Instrumentation. 3. Component-Based Measurement Systems. 4. Object-Oriented Software Engineering. 5. Graphical User Interface Design. 6. Database Management. 7. Software Testing. Part II. Real-World Applications. 8. Overview. 9. An Object-Oriented Reconfigurable Software. 10. Flexible Measurement Point Management. 11. A Blending System Using Multithreaded Programming. 12. A Flexible Automatic Test System for Rotating Turbine Machinery. 13. An Internet-Based Online Real-Time Condition Monitoring System. 14. Epilog. Index.

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Book SynopsisDiagrams communicate relationships more directly and clearly than words ever can. Using only text-based markup, create meaningful and attractive diagrams to document your domain, visualize user flows, reveal system architecture at any desired level, or refactor your code. With the tools and techniques this book will give you, you'll create a wide variety of diagrams in minutes, share them with others, and revise and update them immediately on the basis of feedback. Adding diagrams to your professional vocabulary will enable you to work through your ideas quickly when working on your own code or discussing a proposal with colleagues. Expand your professional vocabulary by learning to communicate with diagrams as easily and naturally as speaking or writing. This book will provide you with the skills and tools to turn ideas into clear, meaningful, and attractive diagrams in mere minutes, using nothing more complicated than text-based markup. You'll learn what kinds of diagrams are suited to each of a variety of use cases, from documenting your domain to understanding how complex code pieces together. Model your software's architecture, creating diagrams focused broadly or narrowly, depending on the audience. Visualize application and user flows, design database schemas, and use diagrams iteratively to design and refactor your application. You'll be able to use technical diagramming to improve your day-to-day workflow. You will better understand the codebase you work in, communicate ideas more effectively and immediately with others, and more clearly document the architecture with C4 diagrams. Manually creating diagrams is cumbersome and time-consuming. You'll learn how to use text-based tools like Mermaid to rapidly turn ideas into diagrams. And You'll learn how to keep your diagrams up to date and seamlessly integrated into your engineering workflow. You'll be better at visualizing and communicating when you add diagrams to your standard vocabulary. What You Need: A Mac or PC A GitHub account

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Book SynopsisChapter 1: Containers.- Chapter 2: Command line.- Chapter 3: Coding introduction.- Chapter 4: AI's role in coding.- Part I: Designing Your Software.- Chapter 5: Initial project design.- Chapter 6: Database Design.- Chapter 7: Object Orientation.- Chapter 8: Flow Diagrams.- Chapter 9: AI's Role in Software Design.- Part II: Building Your Software.- Chapter 10: Software Patterns.- Chapter 11: Coding Principles.- Chapter 12: AI's role in patterns and principles.- Part III: Deploying Your Software.- Chapter 13: Source Control and Deployments.- Chapter 14: Security.- Chapter 15: Hosting and Cloud-based technology.- Part IV: Testing Your Software.- Chapter 16: Reviews and Automated Testing.- Chapter 17: The Role of AI in Security and Testing.

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