Pattern Classification


David G. Stork - 1973
    Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

Professional Android 4 Application Development


Reto Meier - 2012
    If you're anexperienced developer, you can start creating robust mobile Androidapps right away with this professional guide to Android 4application development. Written by one of Google's lead Androiddeveloper advocates, this practical book walks you through a seriesof hands-on projects that illustrate the features of the AndroidSDK. That includes all the new APIs introduced in Android 3 and 4, including building for tablets, using the Action Bar, Wi-Fi Direct, NFC Beam, and more.Shows experienced developers how to create mobile applicationsfor Android smartphones and tabletsRevised and expanded to cover all the Android SDK releasesincluding Android 4.0 (Ice Cream Sandwich), including all updatedAPIs, and the latest changes to the Android platform.Explains new and enhanced features such as drag and drop, fragments, the action bar, enhanced multitouch support, newenvironmental sensor support, major improvements to the animationframework, and a range of new communications techniques includingNFC and Wi-Fi direct.Provides practical guidance on publishing and marketing yourapplications, best practices for user experience, and moreThis book helps you learn to master the design, lifecycle, andUI of an Android app through practical exercises, which you canthen use as a basis for developing your own Android apps.

Problem Solving with Algorithms and Data Structures Using Python


Bradley N. Miller - 2005
    It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. Even though the second course is considered more advanced than the first course, this book assumes you are beginners at this level. You may still be struggling with some of the basic ideas and skills from a first computer science course and yet be ready to further explore the discipline and continue to practice problem solving. We cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

Reinforcement Learning: An Introduction


Richard S. Sutton - 1998
    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.

Modern Perl


chromatic - 2010
    With countless satisfied developers, tens of thousands of freely available libraries, and continual improvements to the language and its ecosystem, modern Perl development can be easy, reliable, and fun. To take advantage of the full power of Perl 5--to become a true expert, capable of solving any problem put before you--you must understand the language. Modern Perl explains Perl 5 from theory to implementation, including Perl 5.12.

Streaming Systems


Tyler Akidau - 2018
    As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way.Expanded from Tyler Akidau's popular blog posts Streaming 101 and Streaming 102, this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You'll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax.You'll explore:How streaming and batch data processing patterns compareThe core principles and concepts behind robust out-of-order data processingHow watermarks track progress and completeness in infinite datasetsHow exactly-once data processing techniques ensure correctnessHow the concepts of streams and tables form the foundations of both batch and streaming data processingThe practical motivations behind a powerful persistent state mechanism, driven by a real-world exampleHow time-varying relations provide a link between stream processing and the world of SQL and relational algebra

How to Lie with Statistics


Darrell Huff - 1954
    Darrell Huff runs the gamut of every popularly used type of statistic, probes such things as the sample study, the tabulation method, the interview technique, or the way the results are derived from the figures, and points up the countless number of dodges which are used to fool rather than to inform.

Algorithms


Robert Sedgewick - 1983
    This book surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use.The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts.The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants.Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.

Bayes Theorem: A Visual Introduction For Beginners


Dan Morris - 2016
    Bayesian statistics is taught in most first-year statistics classes across the nation, but there is one major problem that many students (and others who are interested in the theorem) face. The theorem is not intuitive for most people, and understanding how it works can be a challenge, especially because it is often taught without visual aids. In this guide, we unpack the various components of the theorem and provide a basic overview of how it works - and with illustrations to help. Three scenarios - the flu, breathalyzer tests, and peacekeeping - are used throughout the booklet to teach how problems involving Bayes Theorem can be approached and solved. Over 60 hand-drawn visuals are included throughout to help you work through each problem as you learn by example. The illustrations are simple, hand-drawn, and in black and white. For those interested, we have also included sections typically not found in other beginner guides to Bayes Rule. These include: A short tutorial on how to understand problem scenarios and find P(B), P(A), and P(B|A). For many people, knowing how to approach scenarios and break them apart can be daunting. In this booklet, we provide a quick step-by-step reference on how to confidently understand scenarios.A few examples of how to think like a Bayesian in everyday life. Bayes Rule might seem somewhat abstract, but it can be applied to many areas of life and help you make better decisions. It is a great tool that can help you with critical thinking, problem-solving, and dealing with the gray areas of life. A concise history of Bayes Rule. Bayes Theorem has a fascinating 200+ year history, and we have summed it up for you in this booklet. From its discovery in the 1700’s to its being used to break the German’s Enigma Code during World War 2, its tale is quite phenomenal.Fascinating real-life stories on how Bayes formula is used in everyday life.From search and rescue to spam filtering and driverless cars, Bayes is used in many areas of modern day life. We have summed up 3 examples for you and provided an example of how Bayes could be used.An expanded definitions, notations, and proof section.We have included an expanded definitions and notations sections at the end of the booklet. In this section we define core terms more concretely, and also cover additional terms you might be confused about. A recommended readings section.From The Theory That Would Not Die to a few other books, there are a number of recommendations we have for further reading. Take a look! If you are a visual learner and like to learn by example, this intuitive booklet might be a good fit for you. Bayesian statistics is an incredibly fascinating topic and likely touches your life every single day. It is a very important tool that is used in data analysis throughout a wide-range of industries - so take an easy dive into the theorem for yourself with a visual approach!If you are looking for a short beginners guide packed with visual examples, this booklet is for you.

Artificial Intelligence: A Guide for Thinking Humans


Melanie Mitchell - 2019
    The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it.In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go.Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.

Pro Drupal Development


John K. VanDyk - 2007
    With it, one can create a variety of community-driven sites, including blogs, forums, wiki-style sites, and much more. Assuming that users already possess the knowledge to install and bring a standard installation online, the authors delve into Drupal internals, showing how to truly take advantage of its powerful architecture.

Hacker's Delight


Henry S. Warren Jr. - 2002
    Aiming to tell the dark secrets of computer arithmetic, this title is suitable for library developers, compiler writers, and lovers of elegant hacks.

Practical Object Oriented Design in Ruby


Sandi Metz - 2012
    The Web is awash in Ruby code that is now virtually impossible to change or extend. This text helps you solve that problem by using powerful real-world object-oriented design techniques, which it thoroughly explains using simple and practical Ruby examples. Sandi Metz has distilled a lifetime of conversations and presentations about object-oriented design into a set of Ruby-focused practices for crafting manageable, extensible, and pleasing code. She shows you how to build new applications that can survive success and repair existing applications that have become impossible to change. Each technique is illustrated with extended examples, all downloadable from the companion Web site, poodr.info. The first title to focus squarely on object-oriented Ruby application design, Practical Object-Oriented Design in Ruby will guide you to superior outcomes, whatever your previous Ruby experience. Novice Ruby programmers will find specific rules to live by; intermediate Ruby programmers will find valuable principles they can flexibly interpret and apply; and advanced Ruby programmers will find a common language they can use to lead development and guide their colleagues. This guide will help you Understand how object-oriented programming can help you craft Ruby code that is easier to maintain and upgrade Decide what belongs in a single Ruby class Avoid entangling objects that should be kept separate Define flexible interfaces among objects Reduce programming overhead costs with duck typing Successfully apply inheritance Build objects via composition Design cost-effective tests Solve common problems associated with poorly designed Ruby code

Python: Programming: Your Step By Step Guide To Easily Learn Python in 7 Days (Python for Beginners, Python Programming for Beginners, Learn Python, Python Language)


iCode Academy - 2017
    Are You Ready To Learn Python Easily? Learning Python Programming in 7 days is possible, although it might not look like it

802.11 Wireless Networks: The Definitive Guide


Matthew S. Gast - 2002
    Foremost on that list is mobility, since going wireless frees you from the tether of an Ethernet cable at a desk. But that's just the tip of the cable-free iceberg. Wireless networks are also more flexible, faster and easier for you to use, and more affordable to deploy and maintain.The de facto standard for wireless networking is the 802.11 protocol, which includes Wi-Fi (the wireless standard known as 802.11b) and its faster cousin, 802.11g. With easy-to-install 802.11 network hardware available everywhere you turn, the choice seems simple, and many people dive into wireless computing with less thought and planning than they'd give to a wired network. But it's wise to be familiar with both the capabilities and risks associated with the 802.11 protocols. And 802.11 Wireless Networks: The Definitive Guide, 2nd Edition is the perfect place to start.This updated edition covers everything you'll ever need to know about wireless technology. Designed with the system administrator or serious home user in mind, it's a no-nonsense guide for setting up 802.11 on Windows and Linux. Among the wide range of topics covered are discussions on:deployment considerationsnetwork monitoring and performance tuningwireless security issueshow to use and select access pointsnetwork monitoring essentialswireless card configurationsecurity issues unique to wireless networksWith wireless technology, the advantages to its users are indeed plentiful. Companies no longer have to deal with the hassle and expense of wiring buildings, and households with several computers can avoid fights over who's online. And now, with 802.11 Wireless Networks: The Definitive Guide, 2nd Edition, you can integrate wireless technology into your current infrastructure with the utmost confidence.