Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    Based on two popular talks from author Lea Verou--including "CSS3 Secrets: 10 things you may not know about CSS"--this practical guide provides intermediate to advanced CSS developers with more than 40 undocumented techniques and tips for using CSS3 to create better websites.The talks that spawned this book have been top-rated by attendees in every conference they were presented, and praised in industry media such as ."net" magazine.Get information you won't find in any other bookLearn through small, easily digestible chaptersHelps you understand CSS more deeply so you can improve your own solutionsApply Lea's techniques to practically every CSS problem you faceGain tips from a rockstar author who serves as an Invited Expert in W3C's CSS Working Group

    And code. And code. You build only to rebuild. You focus on making your site compatible with almost every browser or wireless device ever put out there. Then along comes a new device or a new browser, and you start all over again.You can get off the merry-go-round.It's time to stop living in the past and get away from the days of spaghetti code, insanely nested table layouts, tags, and other redundancies that double and triple the bandwidth of even the simplest sites. Instead, it's time for forward compatibility.Isn't it high time you started designing with web standards?Standards aren't about leaving users behind or adhering to inflexible rules. Standards are about building sophisticated, beautiful sites that will work as well tomorrow as they do today. You can't afford to design tomorrow's sites with yesterday's piecemeal methods.Jeffrey teaches you to:- Slash design, development, and quality assurance costs (or do great work in spite of constrained budgets)- Deliver superb design and sophisticated functionality without worrying about browser incompatibilities- Set up your site to work as well five years from now as it does today- Redesign in hours instead of days or weeks- Welcome new visitors and make your content more visible to search engines- Stay on the right side of accessibility laws and guidelines- Support wireless and PDA users without the hassle and expense of multiple versions- Improve user experience with faster load times and fewer compatibility headaches- Separate presentation from structure and behavior, facilitating advanced publishing workflows

    The study of type systems--and of programming languages from a type-theoretic perspective--has important applications in software engineering, language design, high-performance compilers, and security.This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material.The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.

    A simple, easy-to-follow guide, illustrated with plenty of full-color examples, this book will lead you through the process of creating great designs from start to finish. Good design principles are not rocket science, and using the information contained in this book will help you create stunning web sites.Understand the design process, from discovery to implementation Understand what makes "good design" Developing pleasing layouts using grids, the rule of thirds, balance and symmetry Use color effectively, develop color schemes and create a palette Use textures, lines, points, shapes, volumes and depth Learn how good typography can make ordinary designs look great Effective imagery: choosing, editing and placing images And much more Throughout the book, you'll follow an example design, from concept to completion, learning along the way. The book's full-color layout and large format (8" x 10") make The Principles Of Beautiful Wed Design a pleasure to read.Editorial Reviews"The Principles of Beautiful Web Design is a good book to kick start your graphic-design journey. The biggest benefit that I got from this book is the knowledge to learn from great designs as opposed to just admiring them in a state of awe." - Slashdot.org"Jason is a great writer, and the book is quite easy to read. It's put together wonderfully, including many full color screenshots and other forms of imagery that make the book a pleasure to read. I'd definitely recommend the book to anyone in Web design." - MondayByNoon"Jason Beaird covers web design in a way that non-designers can understand. He walks you through all of the aspects of design development from initial meeting to finished product. If you are just getting into web development, this is a must read." - Blogcritics.org"This is a thoroughly practical guide to web design that is very well written: good technical depth in easy-to-understand language with excellent illustrations and graphics that support the text. For many users it will be the only web-design text they will need. For those who want to further advance their skills and knowledge it will provide a sound foundation." - PC Update"His "Don't just tell, show!" style makes this book accessible to everyone... It strikes a carefully thought-out balance between describing principles and illustrating them. It is clear and well structured, with practical examples in every chapter." - Mitch Wheat

    We'll use the world's most popular functional programming language: JavaScript. Some may feel this is a poor choice as it's against the grain of the current culture which, at the moment, feels predominately imperative. However, I believe it is the best way to learn FP for several reasons:You likely use it every day at work.This makes it possible to practice and apply your acquired knowledge each day on real world programs rather than pet projects on nights and weekends in an esoteric FP language.We don't have to learn everything up front to start writing programs.In a pure functional language, you cannot log a variable or read a DOM node without using monads. Here we can cheat a little as we learn to purify our codebase. It's also easier to get started in this language since it's mixed paradigm and you can fall back on your current practices while there are gaps in your knowledge.The language is fully capable of writing top notch functional code.We have all the features we need to mimic a language like Scala or Haskell with the help of a tiny library or two. Object-oriented programming currently dominates the industry, but it's clearly awkward in JavaScript. It's akin to camping off of a highway or tap dancing in galoshes. We have to bind all over the place lest this change out from under us, we don't have classes[^Yet], we have various work arounds for the quirky behavior when the new keyword is forgotten, private members are only available via closures. To a lot of us, FP feels more natural anyways.That said, typed functional languages will, without a doubt, be the best place to code in the style presented by this book. JavaScript will be our means of learning a paradigm, where you apply it is up to you. Luckily, the interfaces are mathematical and, as such, ubiquitous. You'll find yourself at home with swiftz, scalaz, haskell, purescript, and other mathematically inclined environments.

    Built for your brain, this book covers C# 3.0 and Visual Studio 2008, and teaches everything from language fundamentals to advanced topics including garbage collection, extension methods, and double-buffered animation. You'll also master C#'s hottest and newest syntax, LINQ, for querying SQL databases, .NET collections, and XML documents. By the time you're through, you'll be a proficient C# programmer, designing and coding large-scale applications. Every few chapters you will come across a lab that lets you apply what you've learned up to that point. Each lab is designed to simulate a professional programming task, increasing in complexity until-at last-you build a working Invaders game, complete with shooting ships, aliens descending while firing, and an animated death sequence for unlucky starfighters. This remarkably engaging book will have you going from zero to 60 with C# in no time flat.

    The aim of The Node Beginner Book is to get you started with developing applications for Node.js, teaching you everything you need to know about advanced JavaScript along the way on 59 pages.

    Even experienced JavaScripters sometimes find themselves overwhelmed as complex apps grow into a tangled web of callbacks.With Async JavaScript, you'll learn about:Event schedulingThe PubSub patternPromises and Deferred objectsFlow control with Async.jsRecipes for common async scenariosMulti-threading with Web WorkersAltJS languagesand more, with examples tailored to jQuery and Node.js.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    For decades, technology leaders have struggled to balance agility, reliability, and security. The consequences of failure have never been greater whether it's the healthcare.gov debacle, cardholder data breaches, or missing the boat with Big Data in the cloud.And yet, high performers using DevOps principles, such as Google, Amazon, Facebook, Etsy, and Netflix, are routinely and reliably deploying code into production hundreds, or even thousands, of times per day.Following in the footsteps of The Phoenix Project, The DevOps Handbook shows leaders how to replicate these incredible outcomes, by showing how to integrate Product Management, Development, QA, IT Operations, and Information Security to elevate your company and win in the marketplace."Table of contentsPrefaceSpreading the Aha! MomentIntroductionPART I: THE THREE WAYS1. Agile, continuous delivery and the three ways2. The First Way: The Principles of Flow3. The Second Way: The Principle of Feedback4. The Third Way: The Principles of Continual LearningPART II: WHERE TO START5. Selecting which value stream to start with6. Understanding the work in our value stream…7. How to design our organization and architecture8. How to get great outcomes by integrating operations into the daily work for developmentPART III: THE FIRST WAY: THE TECHNICAL PRACTICES OF FLOW9. Create the foundations of our deployment pipeline10. Enable fast and reliable automated testing11. Enable and practice continuous integration12. Automate and enable low-risk releases13. Architect for low-risk releasesPART IV: THE SECOND WAY: THE TECHNICAL PRACTICES OF FEEDBACK14*. Create telemetry to enable seeing abd solving problems15. Analyze telemetry to better anticipate problems16. Enable feedbackso development and operation can safely deploy code17. Integrate hypothesis-driven development and A/B testing into our daily work18. Create review and coordination processes to increase quality of our current workPART V: THE THRID WAY: THE TECHNICAL PRACTICES OF CONTINUAL LEARNING19. Enable and inject learning into daily work20. Convert local discoveries into global improvements21. Reserve time to create organizational learning22. Information security as everyone’s job, every day23. Protecting the deployment pipelinePART VI: CONCLUSIONA call to actionConclusion to the DevOps HandbookAPPENDICES1. The convergence of Devops2. The theory of constraints and core chronic conflicts3. Tabular form of downward spiral4. The dangers of handoffs and queues5. Myths of industrial safety6. The Toyota Andon Cord7. COTS Software8. Post-mortem meetings9. The Simian Army10. Transparent uptimeAdditional ResourcesEndnotes

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    But what if you could have your computer do them for you?In "Automate the Boring Stuff with Python," you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand no prior programming experience required. Once you've mastered the basics of programming, you'll create Python programs that effortlessly perform useful and impressive feats of automation to: Search for text in a file or across multiple filesCreate, update, move, and rename files and foldersSearch the Web and download online contentUpdate and format data in Excel spreadsheets of any sizeSplit, merge, watermark, and encrypt PDFsSend reminder emails and text notificationsFill out online formsStep-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.Don't spend your time doing work a well-trained monkey could do. Even if you've never written a line of code, you can make your computer do the grunt work. Learn how in "Automate the Boring Stuff with Python.""

    Over the past few years, incremental developments in core engineering practices for software development have created the foundations for rethinking how architecture changes over time, along with ways to protect important architectural characteristics as it evolves. This practical guide ties those parts together with a new way to think about architecture and time.