Book picks similar to
Logic for Problem Solving, Revisited by Robert Kowalski


artificial-intelligence
computer-science
computing
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Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference


Cameron Davidson-Pilon - 2014
    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

Artificial Intelligence: Structures and Strategies for Complex Problem Solving


George F. Luger - 1997
    It is suitable for a one or two semester university course on AI, as well as for researchers in the field.

Computer Power and Human Reason: From Judgment to Calculation


Joseph Weizenbaum - 1976
    A classic text by the author who developed ELIZA, a natural-language processing system.

Neural Networks: A Comprehensive Foundation


Simon Haykin - 1994
    Introducing students to the many facets of neural networks, this text provides many case studies to illustrate their real-life, practical applications.

The Human Face of Big Data


Rick Smolan - 2012
    Its enable us to sense, measure, and understand aspects of our existence in ways never before possible. The Human Face of Big Data captures, in glorious photographs and moving essays, an extraordinary revolution sweeping, almost invisibly, through business, academia, government, healthcare, and everyday life. It's already enabling us to provide a healthier life for our children. To provide our seniors with independence while keeping them safe. To help us conserve precious resources like water and energy. To alert us to tiny changes in our health, weeks or years before we develop a life-threatening illness. To peer into our own individual genetic makeup. To create new forms of life.  And soon, as many predict, to re-engineer our own species. And we've barely scratched the surface . . . Over the past decade, Rick Smolan and Jennifer Erwitt, co-founders of Against All Odds Productions, have produced a series of ambitious global projects in collaboration with hundreds of the world's leading photographers, writers, and graphic designers. Their Day in the Life projects were credited for creating a mass market for large-format illustrated books (rare was the coffee table book without one).  Today their projects aim at sparking global conversations about emerging topics ranging from the Internet (24 Hours in Cyberspace), to Microprocessors (One Digital Day), to how the human race is learning to heal itself, (The Power to Heal) to the global water crisis (Blue Planet Run). This year Smolan and Erwitt dispatched photographers and writers in every corner of the globe to explore the world of “Big Data” and to determine if it truly does, as many in the field claim, represent a brand new toolset for humanity, helping address the biggest challenges facing our species. The book features 10 essays by noted writers:Introduction: OCEANS OF DATA by Dan GardnerChapter 1: REFLECTIONS IN A DIGITAL MIRROR by Juan Enriquez, CEO, BiotechnomomyChapter 2: OUR DATA OURSELVES by Kate Green, the EconomistChapter 3: QUANTIFYING MYSELF by AJ Jacobs, EsquireChapter 4: DARK DATA by Marc Goodman, Future Crime InstituteChapter 5:  THE SENTIENT SENSOR MESH by Susan Karlin, Fast CompanyChapter 6: TAKING THE PULSE OF THE PLANET by Esther Dyson, EDventureChapter 7: CITIZEN SCIENCE by Gareth Cook, the Boston GlobeChapter 8: A DEMOGRAPH OF ONE by Michael Malone, Forbes magazineChapter 9: THE ART OF DATA by Aaron Koblin, Google Artist in ResidenceChapter 10: DATA DRIVEN by Jonathan Harris, Cowbird The book will also feature stunning info graphics from NIGEL HOLMES.1) GOOGLING GOOGLE: all the ways Google uses Data to help humanity2) DATA IS THE NEW OIL3) THE WORLD ACCORDING TO TWITTER4) AUCTIONING EYEBALLS: The world of Internet advertising5) FACEBOOK: A Billion Friends

Distributed Systems For Fun and Profit


Mikito Takada - 2013
    

The Society of Mind


Marvin Minsky - 1985
    Mirroring his theory, Minsky boldly casts The Society of Mind as an intellectual puzzle whose pieces are assembled along the way. Each chapter -- on a self-contained page -- corresponds to a piece in the puzzle. As the pages turn, a unified theory of the mind emerges, like a mosaic. Ingenious, amusing, and easy to read, The Society of Mind is an adventure in imagination.

Domain-Specific Languages


Martin Fowler - 2010
    In Domain-Specific Languages , noted software development expert Martin Fowler first provides the information software professionals need to decide if and when to utilize DSLs. Then, where DSLs prove suitable, Fowler presents effective techniques for building them, and guides software engineers in choosing the right approaches for their applications. This book's techniques may be utilized with most modern object-oriented languages; the author provides numerous examples in Java and C#, as well as selected examples in Ruby. Wherever possible, chapters are organized to be self-standing, and most reference topics are presented in a familiar patterns format. Armed with this wide-ranging book, developers will have the knowledge they need to make important decisions about DSLs--and, where appropriate, gain the significant technical and business benefits they offer. The topics covered include: - How DSLs compare to frameworks and libraries, and when those alternatives are sufficient - Using parsers and parser generators, and parsing external DSLs - Understanding, comparing, and choosing DSL language constructs - Determining whether to use code generation, and comparing code generation strategies - Previewing new language workbench tools for creating DSLs

Understanding the Linux Kernel


Daniel P. Bovet - 2000
    The kernel handles all interactions between the CPU and the external world, and determines which programs will share processor time, in what order. It manages limited memory so well that hundreds of processes can share the system efficiently, and expertly organizes data transfers so that the CPU isn't kept waiting any longer than necessary for the relatively slow disks.The third edition of Understanding the Linux Kernel takes you on a guided tour of the most significant data structures, algorithms, and programming tricks used in the kernel. Probing beyond superficial features, the authors offer valuable insights to people who want to know how things really work inside their machine. Important Intel-specific features are discussed. Relevant segments of code are dissected line by line. But the book covers more than just the functioning of the code; it explains the theoretical underpinnings of why Linux does things the way it does.This edition of the book covers Version 2.6, which has seen significant changes to nearly every kernel subsystem, particularly in the areas of memory management and block devices. The book focuses on the following topics:Memory management, including file buffering, process swapping, and Direct memory Access (DMA)The Virtual Filesystem layer and the Second and Third Extended FilesystemsProcess creation and schedulingSignals, interrupts, and the essential interfaces to device driversTimingSynchronization within the kernelInterprocess Communication (IPC)Program executionUnderstanding the Linux Kernel will acquaint you with all the inner workings of Linux, but it's more than just an academic exercise. You'll learn what conditions bring out Linux's best performance, and you'll see how it meets the challenge of providing good system response during process scheduling, file access, and memory management in a wide variety of environments. This book will help you make the most of your Linux system.

Graph Databases


Ian Robinson - 2013
    With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems.Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution.Model data with the Cypher query language and property graph modelLearn best practices and common pitfalls when modeling with graphsPlan and implement a graph database solution in test-driven fashionExplore real-world examples to learn how and why organizations use a graph databaseUnderstand common patterns and components of graph database architectureUse analytical techniques and algorithms to mine graph database information

The Model Thinker: What You Need to Know to Make Data Work for You


Scott E. Page - 2018
    But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.

Linux Device Drivers


Jonathan Corbet - 2005
    And writing device drivers is one of the few areas of programming for the Linux operating system that calls for unique, Linux-specific knowledge. For years now, programmers have relied on the classic "Linux Device Drivers" from O'Reilly to master this critical subject. Now in its third edition, this bestselling guide provides all the information you'll need to write drivers for a wide range of devices.Over the years the book has helped countless programmers learn: how to support computer peripherals under the Linux operating system how to develop and write software for new hardware under Linux the basics of Linux operation even if they are not expecting to write a driver The new edition of "Linux Device Drivers" is better than ever. The book covers all the significant changes to Version 2.6 of the Linux kernel, which simplifies many activities, and contains subtle new features that can make a driver both more efficient and more flexible. Readers will find new chapters on important types of drivers not covered previously, such as consoles, USB drivers, and more.Best of all, you don't have to be a kernel hacker to understand and enjoy this book. All you need is an understanding of the C programming language and some background in Unix system calls. And for maximum ease-of-use, the book uses full-featured examples that you can compile and run without special hardware.Today Linux holds fast as the most rapidly growing segment of the computer market and continues to win over enthusiastic adherents in many application areas. With this increasing support, Linux is now absolutely mainstream, and viewed as a solid platform for embedded systems. If you're writing device drivers, you'll want this book. In fact, you'll wonder how drivers are ever written without it.

A Discipline of Programming


Edsger W. Dijkstra - 1976
    

CCNA Routing and Switching Study Guide: Exams 100-101, 200-101, and 200-120


Todd Lammle - 2013
    This all-purpose CCNA study guide methodically covers all the objectives of the ICND1 (100-101) and ICND2 (200-101) exams as well as providing additional insight for those taking CCNA Composite (200-120) exam. It thoroughly examines operation of IP data networks, LAN switching technologies, IP addressing (IPv4/IPv6), IP routing technologies, IP services, network device security, troubleshooting, and WAN technologies.Valuable study tools such as a companion test engine that includes hundreds of sample questions, a pre-assessment test, and multiple practice exams. Plus, you'll also get access to hundreds of electronic flashcards, author files, and a network simulator.CCNA candidates may choose to take either the ICND1(100-101) and ICND2 (200-101) exams or the CCNA Composite exam (200-120); this study guide covers the full objectives of all three Written by bestselling Sybex study guide author Todd Lammle, an acknowledged authority on all things Cisco Covers essential Cisco networking topics such as operating an IP data network, IP addressing, switching and routing technologies, troubleshooting, network device security, and much more Includes a comprehensive set of study tools including practice exams, electronic flashcards, comprehensive glossary of key terms, videos, and a network simulator that can be used with the book's hands-on labs Bonus Content: Access to over 40 MicroNugget videos from CBT Nuggets CCNA Routing and Switching Study Guide prepares you for CCNA certification success.

Engineering a Compiler


Keith D. Cooper - 2003
    No longer is execution speed the sole criterion for judging compiled code. Today, code might be judged on how small it is, how much power it consumes, how well it compresses, or how many page faults it generates. In this evolving environment, the task of building a successful compiler relies upon the compiler writer's ability to balance and blend algorithms, engineering insights, and careful planning. Today's compiler writer must choose a path through a design space that is filled with diverse alternatives, each with distinct costs, advantages, and complexities.Engineering a Compiler explores this design space by presenting some of the ways these problems have been solved, and the constraints that made each of those solutions attractive. By understanding the parameters of the problem and their impact on compiler design, the authors hope to convey both the depth of the problems and the breadth of possible solutions. Their goal is to cover a broad enough selection of material to show readers that real tradeoffs exist, and that the impact of those choices can be both subtle and far-reaching.Authors Keith Cooper and Linda Torczon convey both the art and the science of compiler construction and show best practice algorithms for the major passes of a compiler. Their text re-balances the curriculum for an introductory course in compiler construction to reflect the issues that arise in current practice.