Windows Presentation Foundation (WPF) is the recommended technology for creating Windows user interfaces, giving you the power to create richer and more compelling applications than you dreamed possible. Whether you want to develop traditional user interfaces or integrate 3D graphics, audio/video, animation, dynamic skinning, multi-touch, rich document support, speech recognition, or more, WPF enables you to do so in a seamless, resolution-independent manner. WPF 4 Unleashed is the authoritative book that covers it all, in a practical and approachable fashion, authored by WPF guru and Microsoft developer Adam Nathan. Covers everything you need to know about Extensible Application Markup Language (XAML) Examines the WPF feature areas in incredible depth: controls, layout, resources, data binding, styling, graphics, animation, and more Highlights the latest features, such as multi-touch, text rendering improvements, XAML language enhancements, new controls, the Visual State Manager, easing functions, and much more Delves into topics that aren't covered by most books: 3D, speech, audio/video, documents, effects Shows how to create popular UI elements, such as Galleries, ScreenTips, and more Demonstrates how to create sophisticated UI mechanisms, such as Visual Studio-like collapsible/dockable panes Explains how to create first-class custom controls for WPF Demonstrates how to create hybrid WPF software that leverages Windows Forms, DirectX, ActiveX, or other non-WPF technologies Explains how to exploit new Windows 7 features, such as Jump Lists and taskbar customizations

    Mastering this art will not only make you the most desired developer in the market, but it will transform the craziest deadline into "Consider it done, Sir".

    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

    As a modern application developer you need to understand the emerging field of data management, both RDBMS and NoSQL. Seven Databases in Seven Weeks takes you on a tour of some of the hottest open source databases today. In the tradition of Bruce A. Tate's Seven Languages in Seven Weeks, this book goes beyond your basic tutorial to explore the essential concepts at the core each technology. Redis, Neo4J, CouchDB, MongoDB, HBase, Riak and Postgres. With each database, you'll tackle a real-world data problem that highlights the concepts and features that make it shine. You'll explore the five data models employed by these databases-relational, key/value, columnar, document and graph-and which kinds of problems are best suited to each. You'll learn how MongoDB and CouchDB are strikingly different, and discover the Dynamo heritage at the heart of Riak. Make your applications faster with Redis and more connected with Neo4J. Use MapReduce to solve Big Data problems. Build clusters of servers using scalable services like Amazon's Elastic Compute Cloud (EC2). Discover the CAP theorem and its implications for your distributed data. Understand the tradeoffs between consistency and availability, and when you can use them to your advantage. Use multiple databases in concert to create a platform that's more than the sum of its parts, or find one that meets all your needs at once.Seven Databases in Seven Weeks will take you on a deep dive into each of the databases, their strengths and weaknesses, and how to choose the ones that fit your needs.What You Need: To get the most of of this book you'll have to follow along, and that means you'll need a *nix shell (Mac OSX or Linux preferred, Windows users will need Cygwin), and Java 6 (or greater) and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.

    With this practical book, you'll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You'll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You'll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media.Learn how to apply the tidy text format to NLPUse sentiment analysis to mine the emotional content of textIdentify a document's most important terms with frequency measurementsExplore relationships and connections between words with the ggraph and widyr packagesConvert back and forth between R's tidy and non-tidy text formatsUse topic modeling to classify document collections into natural groupsExamine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages

    The focus is on SQL-it covers all major SQL databases without getting lost in the details of any one specific product. Starting with the basics of indexing and the WHERE clause, SQL Performance Explained guides developers through all parts of an SQL statement and explains the pitfalls of object-relational mapping (ORM) tools like Hibernate. Topics covered include: Using multi-column indexes; Correctly applying SQL functions; Efficient use of LIKE queries; Optimizing join operations; Clustering data to improve performance; Pipelined execution of ORDER BY and GROUP BY; Getting the best performance for pagination queries; Understanding the scalability of databases. Its systematic structure makes SQL Performance Explained both a textbook and a reference manual that should be on every developer's bookshelf.

    Not only will you learn about the enterprise class features in the 9.2 release, you’ll also discover that PostgeSQL is more than just a database system—it’s also an impressive application platform.With numerous examples throughout this book, you’ll learn how to achieve tasks that are difficult or impossible in other databases. If you’re an existing PostgreSQL user, you’ll pick up gems you may have missed along the way.Learn basic administration tasks, such as role management, database creation, backup, and restoreApply the psql command-line utility and the pgAdmin graphical administration toolExplore PostgreSQL tables, constraints, and indexesLearn powerful SQL constructs not generally found in other databasesUse several different languages to write database functionsTune your queries to run as fast as your hardware will allowQuery external and variegated data sources with Foreign Data WrappersLearn how to replicate data, using built-in replication features

    The vision behind Clojure is of a radically simple language framework holding together a sophisticated collection of programming features. Learning Clojure involves much more than just learning the mechanics of the language. To really get Clojure you need to understand the ideas underlying this structure of framework and features. You need this book: an accessible introduction to Clojure that focuses on the ideas behind the language as well as the practical details of writing code.

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

     AWS has been the frontrunner in cloud computing products and services, and the AWS Certified Solutions Architect Official Study Guide for the Associate exam will get you fully prepared through expert content, and real-world knowledge, key exam essentials, chapter review questions, access to Sybex’s interactive online learning environment, and much more. This official study guide, written by AWS experts, covers exam concepts, and provides key review on exam topics, including: Mapping Multi-Tier Architectures to AWS Services, such as web/app servers, firewalls, caches and load balancers Understanding managed RDBMS through AWS RDS (MySQL, Oracle, SQL Server, Postgres, Aurora) Understanding Loose Coupling and Stateless Systems Comparing Different Consistency Models in AWS Services Understanding how AWS CloudFront can make your application more cost efficient, faster and secure Implementing Route tables, Access Control Lists, Firewalls, NAT, and DNS Applying AWS Security Features along with traditional Information and Application Security Using Compute, Networking, Storage, and Database AWS services Architecting Large Scale Distributed Systems Understanding of Elasticity and Scalability Concepts Understanding of Network Technologies Relating to AWS Deploying and Managing Services with tools such as CloudFormation, OpsWorks and Elastic Beanstalk. Learn from the AWS subject-matter experts, review with proven study tools, and apply real-world scenarios. If you are looking to take the AWS Certified Solutions Architect Associate exam, this guide is what you need for comprehensive content and robust study tools that will help you gain the edge on exam day and throughout your career.

    As scale and demand increase, so does Complexity. Fortunately, scalability and simplicity are not mutually exclusive—rather than using some trendy technology, a different approach is needed. Big data systems use many machines working in parallel to store and process data, which introduces fundamental challenges unfamiliar to most developers.Big Data shows how to build these systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy to understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to use them in practice, and how to deploy and operate them once they're built.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

    What You Will Learn - Write clean and maintainable code - Create reusable components applying consolidated techniques - Use React effectively in the browser and node - Choose the right styling approach according to the needs of the applications - Use server-side rendering to make applications load faster - Build high-performing applications by optimizing components In Detail Taking a complete journey through the most valuable design patterns in React, this book demonstrates how to apply design patterns and best practices in real-life situations, whether that's for new or already existing projects. It will help you to make your applications more flexible, perform better, and easier to maintain - giving your workflow a huge boost when it comes to speed without reducing quality. We'll begin by understanding the internals of React before gradually moving on to writing clean and maintainable code. We'll build components that are reusable across the application, structure applications, and create forms that actually work. Then we'll style React components and optimize them to make applications faster and more responsive. Finally, we'll write tests effectively and you'll learn how to contribute to React and its ecosystem. By the end of the book, you'll be saved from a lot of trial and error and developmental headaches, and you will be on the road to becoming a React expert. Style and approach The design patterns in the book are explained using real-world, step-by-step examples. For each design pattern, there are hints about when to use it and when to look for something more suitable. This book can also be used as a practical guide, showing you how to leverage design patterns.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Learn Java Programming Fast with a unique Hands-On Project. Book 4 of the Learn Coding Fast Series. Covers Java 8. Have you always wanted to learn computer programming but are afraid it'll be too difficult for you? Or perhaps you know other programming languages but are interested in learning the Java language fast? This book is for you. You no longer have to waste your time and money trying to learn Java from boring books that are 600 pages long, expensive online courses or complicated Java tutorials that just leave you more confused and frustrated. What this book offers... Java for Beginners Complex concepts are broken down into simple steps to ensure that you can easily master the Java language even if you have never coded before. Carefully Chosen Java Examples Examples are carefully chosen to illustrate all concepts. In addition, the output for all examples are provided immediately so you do not have to wait till you have access to your computer to test the examples. Careful selection of topics Topics are carefully selected to give you a broad exposure to Java, while not overwhelming you with information overload. These topics include object-oriented programming concepts, error handling techniques, file handling techniques and more. In addition, new features in Java (such as lambda expressions and default methods etc) are also covered so that you are always up to date with the latest advancement in the Java language. Learn The Java Programming Language Fast Concepts are presented in a "to-the-point" style to cater to the busy individual. You no longer have to endure boring and lengthy Java textbooks that simply puts you to sleep. With this book, you can learn Java fast and start coding immediately. How is this book different... The best way to learn Java is by doing. This book includes a unique project at the end of the book that requires the application of all the concepts taught previously. Working through the project will not only give you an immense sense of achievement, it’ll also help you retain the knowledge and master the language. Are you ready to dip your toes into the exciting world of Java coding? This book is for you. Click the BUY button and download it now. What you'll learn: Introduction to Java - What is Java? - What software do you need to code Java programs? - How to install and run JDK and Netbeans? Data types and Operators - What are the eight primitive types in Java? - What are arrays and lists? - How to format Java strings - What is a primitive type vs reference type? - What are the common Java operators? Object Oriented Programming - What is object oriented programming? - How to write your own classes - What are fields, methods and constructors? - What is encapsulation, inheritance and polymorphism? - What is an abstract class and interface? Controlling the Flow of a Program - What are condition statements? - How to use control flow statements in Java - How to handle errors and exceptions - How to throw your own exception

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect