It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpayd�n offers a concise and accessible overview of the new AI. This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias. Alpayd�n, author of a popular textbook on machine learning, explains that as Big Data has gotten bigger, the theory of machine learning--the foundation of efforts to process that data into knowledge--has also advanced. He describes the evolution of the field, explains important learning algorithms, and presents example applications. He discusses the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances; and reinforcement learning, when an autonomous agent learns to take actions to maximize reward. In a new chapter, he considers transparency, explainability, and fairness, and the ethical and legal implications of making decisions based on data.

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

    Learn how to leverage the Django web framework to its full potential in this advanced tutorial and reference. Endorsed by Django, Pro Django more or less picks up where The Definitive Guide to Django left off and examines in greater detail the unusual and complex problems that Python web application developers can face and how to solve them.Provides in-depth information about advanced tools and techniques available in every Django installation Runs the gamut from the theory of Django's internal operations to actual code that solves real-world problems for high-volume environments Goes above and beyond other books, leaving the basics behind Shows how Django can do things even its core developers never dreamed possible

    Ideal as a quick reference, Regular Expression Pocket Reference covers the regular expression APIs for Perl 5.8, Ruby (including some upcoming 1.9 features), Java, PHP, .NET and C#, Python, vi, JavaScript, and the PCRE regular expression libraries. This concise and easy-to-use reference puts a very powerful tool for manipulating text and data right at your fingertips. Composed of a mixture of symbols and text, regular expressions can be an outlet for creativity, for brilliant programming, and for the elegant solution. Regular Expression Pocket Reference offers an introduction to regular expressions, pattern matching, metacharacters, modes and constructs, and then provides separate sections for each of the language APIs, with complete regex listings including:Supported metacharacters for each language API Regular expression classes and interfaces for Ruby, Java, .NET, and C# Regular expression operators for Perl 5.8 Regular expression module objects and functions for Python Pattern-matching functions for PHP and the vi editor Pattern-matching methods and objects for JavaScript Unicode Support for each of the languages With plenty of examples and other resources, Regular Expression Pocket Reference summarizes the complex rules for performing this critical text-processing function, and presents this often-confusing topic in a friendly and well-organized format. This guide makes an ideal on-the-job companion.

    

    Intended for developers who are already familiar with the Apex language, and experienced Java and C# developers who are moving to Apex, this book starts where the Force.com documentation leaves off. Instead of trying to cover all of the features of the platform, Advanced Apex programming focuses entirely on the Apex language and core design patterns. You’ll learn how to truly think in Apex – to embrace limits and bulk patterns. You’ll see how to develop architectures for efficient and reliable trigger handling, and for asynchronous operations. You’ll discover that best practices differ radically depending on whether you are building software for a specific organization or for a managed package. And you’ll find approaches for incorporating testing and diagnostic code that can dramatically improve the reliability and deployment of Apex software, and reduce your lifecycle and support costs. Based on his experience both as a consultant and as architect of a major AppExchange package, Dan Appleman focuses on the real-world problems and issues that are faced by Apex developers every day, along with the obscure problems and surprises that can sneak up on you if you are unprepared.

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Four case studies illustrate applications of category theory to programming language design, semantics, and the solution of recursive domain equations. A brief literature survey offers suggestions for further study in more advanced texts.

    You d be up to your neck in normal forms before you even had a chance to wade. When Michael J. Hernandez needed a database design book to teach mere mortals like himself, there were none. So he began a personal quest to learn enough to write one. And he did.Now in its Second Edition, Database Design for Mere Mortals is a miracle for today s generation of database users who don t have the background -- or the time -- to learn database design the hard way. It s also a secret pleasure for working pros who are occasionally still trying to figure out what they were taught.Drawing on 13 years of database teaching experience, Hernandez has organized database design into several key principles that are surprisingly easy to understand and remember. He illuminates those principles using examples that are generic enough to help you with virtually any application.Hernandez s goals are simple. You ll learn how to create a sound database structure as easily as possible. You ll learn how to optimize your structure for efficiency and data integrity. You ll learn how to avoid problems like missing, incorrect, mismatched, or inaccurate data. You ll learn how to relate tables together to make it possible to get whatever answers you need in the future -- even if you haven t thought of the questions yet.If -- as is often the case -- you already have a database, Hernandez explains how to analyze it -- and leverage it. You ll learn how to identify new information requirements, determine new business rules that need to be applied, and apply them.Hernandez starts with an introduction to databases, relational databases, and the idea and objectives of database design. Next, you ll walk through the key elements of the database design process: establishing table structures and relationships, assigning primary keys, setting field specifications, and setting up views. Hernandez s extensive coverage of data integrity includes a full chapter on establishing business rules and using validation tables.Hernandez surveys bad design techniques in a chapter on what not to do -- and finally, helps you identify those rare instances when it makes sense to bend or even break the conventional rules of database design.There s plenty that s new in this edition. Hernandez has gone over his text and illustrations with a fine-tooth comb to improve their already impressive clarity. You ll find updates to reflect new advances in technology, including web database applications. There are expanded and improved discussions of nulls and many-to-many relationships; multivalued fields; primary keys; and SQL data type fields. There s a new Quick Reference database design flowchart. A new glossary. New review questions at the end of every chapter.Finally, it s worth mentioning what this book isn t. It isn t a guide to any specific database platform -- so you can use it whether you re running Access, SQL Server, or Oracle, MySQL or PostgreSQL. And it isn t an SQL guide. (If that s what you need, Michael J. Hernandez has also coauthored the superb SQL Queries for Mere Mortals). But if database design is what you need to learn, this book s worth its weight in gold. Bill CamardaBill Camarda is a consultant, writer, and web/multimedia content developer. His 15 books include Special Edition Using Word 2000 and Upgrading & Fixing Networks for Dummies, Second Edition.

    An introduction to Python programming for beginners.

    The book begins by introducing the R language, including the development environment. Focusing on practical solutions, the book also offers a crash course in practical statistics and covers elegant methods for dealing with messy and incomplete data using features of R.About the TechnologyR is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data.About the BookR in Action is a language tutorial focused on practical problems. It presents useful statistics examples and includes elegant methods for handling messy, incomplete, and non-normal data that are difficult to analyze using traditional methods. And statistical analysis is only part of the story. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. 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's InsidePractical data analysis, step by stepInterfacing R with other softwareUsing R to visualize dataOver 130 graphsEight reference appendixes================================Table of ContentsPart I Getting startedIntroduction to RCreating a datasetGetting started with graphsBasic data managementAdvanced data managementPart II Basic methodsBasic graphsBasic statisticsPart III Intermediate methodsRegressionAnalysis of variancePower analysisIntermediate graphsRe-sampling statistics and bootstrappingPart IV Advanced methodsGeneralized linear modelsPrincipal components and factor analysisAdvanced methods for missing dataAdvanced graphics

    In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they’ve recovered from nasty data problems.From cranky storage to poor representation to misguided policy, there are many paths to bad data. Bottom line? Bad data is data that gets in the way. This book explains effective ways to get around it.Among the many topics covered, you’ll discover how to:Test drive your data to see if it’s ready for analysisWork spreadsheet data into a usable formHandle encoding problems that lurk in text dataDevelop a successful web-scraping effortUse NLP tools to reveal the real sentiment of online reviewsAddress cloud computing issues that can impact your analysis effortAvoid policies that create data analysis roadblocksTake a systematic approach to data quality analysis

    Master the fundamentals of C++ and object-oriented programming Understand how C++11 features help you write compact and efficient code using concepts such as lambda expressions, move constructors, and assignment operators Learn the Standard Template Library, including containers and algorithms used in most real-world C++ applications Test your knowledge and expertise using exercises at the end of every lesson Learn on your own time, at your own pace: No previous programming experience required Learn C++11, object-oriented programming, and analysis Write fast and powerful C++ programs, compile the source code with a gcc compiler, and create executable files Use the Standard Template Library's (STL) algorithms and containers to write feature-rich yet stable C++ applications Develop sophisticated programming techniques using lambda expressions, smart pointers, and move constructors Learn to expand your program's power with inheritance and polymorphism Master the features of C++ by learning from programming experts Learn C++11 features that allow you to program compact and high-performance C++ applications TABLE OF CONTENTSPART I: THE BASICS LESSON 1: Getting Started with C++11 LESSON 2: The Anatomy of a C++ Program LESSON 3: Using Variables, Declaring Constants LESSON 4: Managing Arrays and Strings LESSON 5: Working with Expressions, Statements, and Operators LESSON 6: Controlling Program Flow LESSON 7: Organizing Code with Functions LESSON 8: Pointers and References Explained PART II: FUNDAMENTALS OF OBJECT-ORIENTED C++ PROGRAMMING LESSON 9: Classes and Objects LESSON 10: Implementing Inheritance LESSON 11: Polymorphism LESSON 12: Operator Types and Operator Overloading LESSON 13: Casting Operators LESSON 14: An Introduction to Macros and Templates PART III: LEARNING THE STANDARD TEMPLATE LIBRARY (STL) LESSON 15: An Introduction to the Standard Template LibraryLESSON 16: The STL String ClassLESSON 17: STL Dynamic Array ClassesLESSON 18: STL list and forward_listLESSON 19: STL Set ClassesLESSON 20: STL Map ClassesPART IV: MORE STL LESSON 21: Understanding Function ObjectsLESSON 22: C++11 Lambda ExpressionsLESSON 23: STL AlgorithmsLESSON 24: Adaptive Containers: Stack and QueueLESSON 25: Working with Bit Flags Using STLPART V: ADVANCED C++ CONCEPTS LESSON 26: Understanding Smart PointersLESSON 27: Using Streams for Input and OutputLESSON 28: Exception HandlingLESSON 29: Going Forward APPENDIXES A: Working with Numbers: Binary and Hexadecimal B: C++ Keywords C: Operator Precedence D: Answers E: ASCII Codes

    What you need to learn to pass a Cisco certification exam such as CCNA and what you need to know to survive in the real world are two very different things. The strategies that this book offers weren 't on the exam, but they 're exactly what you need to do your job well.Network Warrior takes you step by step through the world of hubs, switches, firewalls, and more, including ways to troubleshoot a congested network, and when to upgrade and why. Along the way, you 'll gain an historical perspective of various networking features, such as the way Ethernet evolved. Based on the author 's own experience as well as those he worked for and with, Network Warrior is a Cisco-centric book, focused primarily on the TCP/IP protocol and Ethernet networks -- the realm that Cisco Systems now dominates. The book covers: The type of networks now in use, from LANs, WANs and MANs to CANsThe OSI Model and the layers involved in sending data Hubs, repeaters, switches, and trunks in practice Auto negotiation and why it 's a common problem in network slowdowns Route maps, routing protocols, and switching algorithms in Cisco routers The resilient Ethernet -- how to make things truly redundant Cisco 6500 multi-layer switches and the Catalyst 3750 switch Telecom nomenclature -- why it 's different from the data world T1 and DS3 Firewall theory, designing access lists, authentication in Cisco devices Server load balancing technology Content switch module in action Designing QOS and what QOS does not do IP design and subnetting made easy The book also explains how to sell your ideas to management, how networks become a mess as a company grows, and why change control is your friend. Network Warrior will help network administrators and engineers win the complex battles they face every day.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa