If you're a business or IT professional, this short hands-on guide teaches you how to pull and transform data with SQL in significant ways. You will quickly master the fundamentals of SQL and learn how to create your own databases.Author Thomas Nield provides exercises throughout the book to help you practice your newfound SQL skills at home, without having to use a database server environment. Not only will you learn how to use key SQL statements to find and manipulate your data, but you'll also discover how to efficiently design and manage databases to meet your needs.You'll also learn how to:Explore relational databases, including lightweight and centralized modelsUse SQLite and SQLiteStudio to create lightweight databases in minutesQuery and transform data in meaningful ways by using SELECT, WHERE, GROUP BY, and ORDER BYJoin tables to get a more complete view of your business dataBuild your own tables and centralized databases by using normalized design principlesManage data by learning how to INSERT, DELETE, and UPDATE records

    You want to develop software in the most effective, efficient way possible. This book gives you the answers you’ve been looking for in friendly, clear language.We’ll cover, in depth, the core concepts of Clojure: immutable collections, concurrency, pure functions, and state management. You’ll finally get the complete picture you’ve been looking for, rather than dozens of puzzle pieces you must assemble yourself. First, we focus on Clojure thinking. You’ll discover the simple architecture of Clojure software, effective development processes, and how to structure applications. Next, we explore the core concepts of Clojure development. You’ll learn how to model with immutable data; write simple, pure functions for efficient transformation; build clean, concurrent designs; and structure your code for elegant composition. Finally, we move beyond pure application development and into the real world. You’ll understand your application’s configuration and dependencies, connect with other data sources, and get your libraries and applications out the door.Go beyond the toy box and into Clojure’s way of thinking. By the end of this book, you’ll have the tools and information to put Clojure’s strengths to work.https://pragprog.com/book/vmclojeco/c...

    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.

    PHP is a server-side, HTML-embedded scripting language. It is an open source technology, rapidly gaining popularity as a scripting language for people running dynamic websites. One of its major attractions over Perl, JavaScript and other scripting languages is that PHP has a built-in database integration layer and seamless IP connectivity, with LDAP and TCP as well as the IMAP mail interface. Features; Real world, practical experience and techniques From installation and configuration of the PHP engine to advanced dynamic application design Definitive coverage of core PHP language and database addressing: MySQL is covered in depth. Practical e-commerce and business scripting including database application development, together with PHP and XML applications. LDAP connectivity addressed.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    You’ll learn how each of these platform-agnostic patterns work, when they might be useful in the cloud, and what impact they’ll have on your application architecture. You’ll also see an example of each pattern applied to an application built with Windows Azure.The patterns are organized into four major topics, such as scalability and handling failure, and primer chapters provide background on each topic. With the information in this book, you’ll be able to make informed decisions for designing effective cloud-native applications that maximize the value of cloud services, while also paying attention to user experience and operational efficiency.Learn about architectural patterns for:Scalability. Discover the advantages of horizontal scaling. Patterns covered include Horizontally Scaling Compute, Queue-Centric Workflow, and Auto-Scaling.Big data. Learn how to handle large amounts of data across a distributed system. Eventual consistency is explained, along with the MapReduce and Database Sharding patterns.Handling failure. Understand how multitenant cloud services and commodity hardware influence your applications. Patterns covered include Busy Signal and Node Failure.Distributed users. Learn how to overcome delays due to network latency when building applications for a geographically distributed user base. Patterns covered include Colocation, Valet Key, CDN, and Multi-Site Deployment.

    "Machine learning," the process of automating tasks once considered the domain of highly-trained analysts and mathematicians, is the key to efficiently extracting useful information from this sea of raw data. Machine Learning in Action is a unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. In it, the author uses the flexible Python programming language to show how to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification.

    Larman offers a concise, information-packed summary of the key ideas that drive all agile and iterative processes, with the details of four noteworthy iterative methods: Scrum, XP, RUP, and Evo.

    You'll progress from a complete beginner regarding Arduino programming and electronics knowledge to intermediate skills and the confidence to create your own amazing Arduino projects. Absolutely no experience in programming or electronics required!Rather than requiring you to wade through pages of theory before you start making things, this book has a hands-on approach. You will dive into making projects right from the start, learning how to use various electronic components and how to program the Arduino to control or communicate with those components.Each project is designed to build upon the knowledge learned in earlier projects and to further your knowledge in programming as well as skills with electronics. By the end of the book you will be able create your own projects confidently and with creativity.Please note: the print version of this title is black & white; the eBook is full color. You can download the color diagrams in the book from http: //www.apress.com/9781430232407

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

    "The Rails(TM) 3 Way"is the only comprehensive, authoritative guide to delivering production-quality code with Rails 3. Pioneering Rails expert Obie Fernandez and a team of leading experts illuminate the entire Rails 3 API, along with the idioms, design approaches, and libraries that make developing applications with Rails so powerful. Drawing on their unsurpassed experience and track record, they address the real challenges development teams face, showing how to use Rails 3 to maximize your productivity. Using numerous detailed code examples, the author systematically covers Rails 3 key capabilities and subsystems, making this book a reference that you will turn to again and again. He presents advanced Rails programming techniques that have been proven effective in day-to-day usage on dozens of production Rails systems and offers important insights into behavior-driven development and production considerations such as scalability. Dive deep into the Rails 3 codebase and discover why Rails is designed the way it is--and how to make it do what you want it to do.This book will help youLearn what's new in Rails 3 Increase your productivity as a web application developer Realize the overall joy in programming with Rails Leverage Rails' powerful capabilities for building REST-compliant APIs Drive implementation and protect long-term maintainability using RSpec Design and manipulate your domain layer using Active Record Understand and program complex program flows using Action Controller Master sophisticated URL routing concepts Use Ajax techniques via Rails 3 support for unobtrusive JavaScript Learn to extend Rails with popular gems and plugins, and how to write your own Extend Rails with the best third-party plug-ins and write your own Integrate email services into your applications with Action Mailer Improve application responsiveness with background processing Create your own non-Active Record domain classes using Active Model Master Rails' utility classes and extensions in Active Support

    How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates. Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning. Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell Leverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlib Use one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and Storm Learn how to deploy interactive, batch, and streaming applications Connect to data sources including HDFS, Hive, JSON, and S3 Master advanced topics like data partitioning and shared variables

    It discusses the ongoing, international standardization of C++, explores the importance of Clean C code in the common subset of the ISO C and C++ languages, and demonstrates other ways to program in a style that is more compatible with C++.

    As for the latter, are you a programmer and curious about being your own boss? Where do you turn for information? Until now, online and traditional literature havent caught up with the reality of the post-dot com bust.Micro-ISV: From Vision to Reality explains what works and why in today's emerging micro-ISV sector. Currently, thousands of programmers build and deliver great solutions ISV-style, earning success and revenues much larger than you might guess. Written by and for micro-ISVs, with help from some of the leaders of the field, this book takes you beyond just daydreaming to running your own business. It thoroughly explores how it is indeed possible to launch and maintain a small and successful ISV business, and is an ideal read if you're interested in getting started.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.