Book picks similar to
Deep Learning for Computer Architects by Brandon Reagen


machine-learning
system-architecture
artificial-intelligence
computer-engineering

Bayes Theorem Examples: An Intuitive Guide


Scott Hartshorn - 2016
    Essentially, you are estimating a probability, but then updating that estimate based on other things that you know. This book is designed to give you an intuitive understanding of how to use Bayes Theorem. It starts with the definition of what Bayes Theorem is, but the focus of the book is on providing examples that you can follow and duplicate. Most of the examples are calculated in Excel, which is useful for updating probability if you have dozens or hundreds of data points to roll in.

Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms


Jeff Heaton - 2013
    This book teaches basic Artificial Intelligence algorithms such as dimensionality, distance metrics, clustering, error calculation, hill climbing, Nelder Mead, and linear regression. These are not just foundational algorithms for the rest of the series, but are very useful in their own right. The book explains all algorithms using actual numeric calculations that you can perform yourself. Artificial Intelligence for Humans is a book series meant to teach AI to those without an extensive mathematical background. The reader needs only a knowledge of basic college algebra or computer programming—anything more complicated than that is thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, R, Python and C. Other languages planned.

Introduction to Artificial Intelligence and Expert Systems


Dan W. Patterson - 1990
    

Fundamentals of Digital Image Processing


Anil K. Jain - 1988
    Includes a comprehensive chapter on stochastic models for digital image processing. Covers aspects of image representation including luminance, color, spatial and temporal properties of vision, and digitization. Explores various image processing techniques. Discusses algorithm development (software/firmware) for image transforms, enhancement, reconstruction, and image coding.

The Terran Cycle Box Set: Intrinsic, Tempest, Heretic, Legacy


Philip C. Quaintrell - 2019
    He looks like us, he lives like us... but he is not one of us. Kalian knows nothing outside of his mundane life teaching history on 30th century Earth, until a day like any other triggers a series of events, which will tie his fate to that of humanity. A human hand print, embedded into a rock with alien script, is discovered on a moon that mankind has never set foot on. This discovery holds a secret, which will sweep Kalian into the heart of a conspiracy that has corrupted the galaxy for two hundred thousand years.

Machine Learning


Tom M. Mitchell - 1986
    Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.

Machine Learning: Fundamental Algorithms for Supervised and Unsupervised Learning With Real-World Applications


Joshua Chapmann - 2017
    Right?! Machine Learning is a branch of computer science that wants to stop programming computers using a detailed list of commands to follow blindly. Instead, their aim is to implement high-level routines that teach computers how to approach new and unknown problems – these are called algorithms. In practice, they want to give computers the ability to Learn and to Adapt. We can use these algorithms to obtain insights, recognize patterns and make predictions from data, images, sounds or videos we have never seen before – or even knew existed. Unfortunately, the true power and applications of today’s Machine Learning Algorithms remain deeply misunderstood by most people. Through this book I want fix this confusion, I want to shed light on the most relevant Machine Learning Algorithms used in the industry. I will show you exactly how each algorithm works, why it works and when you should use it. Supervised Learning Algorithms K-Nearest Neighbour Naïve Bayes Regressions Unsupervised Learning Algorithms: Support Vector Machines Neural Networks Decision Trees

Multiple View Geometry in Computer Vision


Richard Hartley - 2000
    This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. Richard Hartley and Andrew Zisserman provide comprehensive background material and explain how to apply the methods and implement the algorithms. First Edition HB (2000): 0-521-62304-9

Digital Computer Electronics


Albert Paul Malvino - 1977
    The text relates the fundamentals to three real-world examples: Intel's 8085, Motorola's 6800, and the 6502 chip used by Apple Computers. This edition includes a student version of the TASM cross-assembler software program, experiments for Digital Computer Electronics and more.

A Brief History of Artificial Intelligence: What It Is, Where We Are, and Where We Are Going


Michael Wooldridge - 2021
    As an AI researcher with 25 years of experience, professor Mike Wooldridge has learned to be obsessively cautious about such claims, while still promoting an intense optimism about the future of the field. There have been genuine scientific breakthroughs that have made AI systems possible in the past decade that the founders of the field would have hailed as miraculous. Driverless cars and automated translation tools are just two examples of AI technologies that have become a practical, everyday reality in the past few years, and which will have a huge impact on our world.While the dream of conscious machines remains, Professor Wooldridge believes, a distant prospect, the floodgates for AI have opened. Wooldridge's A Brief History of Artificial Intelligence is an exciting romp through the history of this groundbreaking field--a one-stop-shop for AI's past, present, and world-changing future.

Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition


Dan Jurafsky - 2000
    This comprehensive work covers both statistical and symbolic approaches to language processing; it shows how they can be applied to important tasks such as speech recognition, spelling and grammar correction, information extraction, search engines, machine translation, and the creation of spoken-language dialog agents. The following distinguishing features make the text both an introduction to the field and an advanced reference guide.- UNIFIED AND COMPREHENSIVE COVERAGE OF THE FIELDCovers the fundamental algorithms of each field, whether proposed for spoken or written language, whether logical or statistical in origin.- EMPHASIS ON WEB AND OTHER PRACTICAL APPLICATIONSGives readers an understanding of how language-related algorithms can be applied to important real-world problems.- EMPHASIS ON SCIENTIFIC EVALUATIONOffers a description of how systems are evaluated with each problem domain.- EMPERICIST/STATISTICAL/MACHINE LEARNING APPROACHES TO LANGUAGE PROCESSINGCovers all the new statistical approaches, while still completely covering the earlier more structured and rule-based methods.

The 8088 and 8086 Microprocessors: Programming, Interfacing, Software, Hardware, and Applications


Walter A. Triebel - 1991
    This volume offers thorough, balanced, and practical coverage of both software and hardware topics. Develops basic concepts using the 8088 and 8086 microprocessors, but the 32-bit version of the 80x86 family is also discussed. Examines how to assemble, run, and debug programs, and how to build, test, and troubleshoot interface circuits. Provides detailed coverage of floating-point processing and the single instruction multiple data (DIMD) processing capability of the advanced Pentium processor. Includes added material on number systems, logic functions and operations, conversion between number systems, and addition/subtraction of binary numbers. Includes new advanced material such as floating Point Architecture and Instructions, Multimedia (MMX) Architecture and Instructions, and the hardware and hardware architecture of the Pentium 3 and Pentium 4 processors. Covers the Intel architecture microprocessor families: 8088, 8086, 80286, 80386, 80486, and the latest Pentium(R) processors. Illustrates commands of the DEBUG program and how to assemble, disassemble, load, save, execute, and debug programs on the IBM PC. Introduces the contents of the 8088's instruction set. Explores practical implementation techniques, covering the use of latches, transceivers, buffers, and programmable logic devices in the memory and I/O interfaces of the microcomputer system. A valuable handbook for self-study in learning microprocessors, for electrical engineers, electronic technicians, and all computer programmers.

Digital Integrated Circuits


Jan M. Rabaey - 1995
    Digital Integrated Circuits maintains a consistent, logical flow of subject matter throughout. KEY TOPICS: Addresses today's most significant and compelling industry topics, including: the impact of interconnect, design for low power, issues in timing and clocking, design methodologies, and the tremendous effect of design automation on the digital design perspective. MARKET: For readers interested in digital circuit design.

Artificial Intelligence: 101 Things You Must Know Today About Our Future


Lasse Rouhiainen - 2018
    In fact, AI will dramatically change our entire society.You might have heard that many jobs will be replaced by automation and robots, but did you also know that at the same time a huge number of new jobs will be created by AI?This book covers many fascinating and timely topics related to artificial intelligence, including: self-driving cars, robots, chatbots, and how AI will impact the job market, business processes, and entire industries, just to name a few.This book is divided into ten chapters:Chapter I: Introduction to Artificial IntelligenceChapter II: How Artificial Intelligence Is Changing Many IndustriesChapter III: How Artificial Intelligence Is Changing Business ProcessesChapter IV: Chatbots and How They Will Change CommunicationChapter V: How Artificial Intelligence Is Changing the Job MarketChapter VI: Self-Driving Cars and How They Will Change Traffic as We Know ItChapter VII: Robots and How They Will Change Our LivesChapter VIII: Artificial Intelligence Activities of Big Technology CompaniesChapter IX: Frequently Asked Questions About Artificial Intelligence Part IChapter X: Frequently Asked Questions About Artificial Intelligence Part IITo enhance your learning experience and help make the concepts easier to understand, there are more than 85 visual presentations included throughout the book.You will learn the answers to 101 questions about artificial intelligence, and also have access to a large number of resources, ideas and tips that will help you to understand how artificial intelligence will change our lives.Who is this book for?Managers and business professionalsMarketers and influencersEntrepreneurs and startupsConsultants and coachesEducators and teachersStudents and life-long learnersAnd everyone else who is interested in our future.Are you ready to discover how artificial intelligence will impact your life This guidebook offers a multitude of tools, techniques and strategies that every business and individual can quickly apply and benefit from.

Introductory Circuit Analysis


Robert L. Boylestad - 1968
    Features exceptionally clear explanations and descriptions, step-by-step examples, more than 50 practical applications, over 2000 easy-to-challenging practice problems, and comprehensive coverage of essentials. PSpice, OrCAd version 9.2 Lite Edition, Multisims 2001 version of Electronics Workbench, and MathCad software references and examples are used throughout. Computer programs (C++, BASIC and PSpice) are printed in color, as they run, at the point in the book where they are discussed. Current and Voltage. Resistance. Ohm's Law, Power, and Energy. Series Circuits. Parallel Circuits. Series-Parallel Networks. Methods of Analysis & Selected Topics. Network Theorems. Capacitors. Magnetic Circuits. Inductors. Sinusodial Alternating Waveforms. The Basic Elements and Phasors. Series and Parallel ac Circuits. Series-Parallel ac Networks. Methods of Analysis and Related Topics. Network Theorems (ac). Power (ac). Resonance. Transformers. Polyphase Systems. Decibels, Filters, and Bode Points. Pulse Waveforms and the R-C Response. Nonsinusodial Circuits. System Analysis: An Introduction. For those working in electronic technology.