Book picks similar to
The Scientist and Engineer's Guide to Digital Signal Processing by Steven W. Smith
engineering
science
dsp
technical
Interaction Design: Beyond Human-Computer Interaction
Yvonne Rogers - 2001
It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology
The Swift Programming Language
Apple Inc. - 2014
Swift builds on the best of C and Objective-C, without the constraints of C compatibility. Swift adopts safe programming patterns and adds modern features to make programming easier, more flexible, and more fun. Swift’s clean slate, backed by the mature and much-loved Cocoa and Cocoa Touch frameworks, is an opportunity to reimagine how software development works.
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
Make Your Own Neural Network
Tariq Rashid - 2016
Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.
Time Management for System Administrators: Stop Working Late and Start Working Smart
Thomas A. Limoncelli - 2005
No other job pulls people in so many directions at once. Users interrupt you constantly with requests, preventing you from getting anything done. Your managers want you to get long-term projects done but flood you with reques ... Available here:readmeaway.com/download?i=0596007833Time Management for System Administrators: Stop Working Late and Start Working Smart PDF by Thomas A. LimoncelliRead Time Management for System Administrators: Stop Working Late and Start Working Smart PDF from O'Reilly Media,Thomas A. LimoncelliDownload Thomas A. Limoncelli’s PDF E-book Time Management for System Administrators: Stop Working Late and Start Working Smart
Microservice Patterns
Chris Richardson - 2017
However, successful applications have a habit of growing. Eventually the development team ends up in what is known as monolithic hell. All aspects of software development and deployment become painfully slow. The solution is to adopt the microservice architecture, which structures an application as a services, organized around business capabilities. This architecture accelerates software development and enables continuous delivery and deployment of complex software applications.Microservice Patterns teaches enterprise developers and architects how to build applications with the microservice architecture. Rather than simply advocating for the use the microservice architecture, this clearly-written guide takes a balanced, pragmatic approach. You'll discover that the microservice architecture is not a silver bullet and has both benefits and drawbacks. Along the way, you'll learn a pattern language that will enable you to solve the issues that arise when using the microservice architecture. This book also teaches you how to refactor a monolithic application to a microservice architecture.
Mastering Bitcoin: Unlocking Digital Cryptocurrencies
Andreas M. Antonopoulos - 2014
Whether you're building the next killer app, investing in a startup, or simply curious about the technology, this practical book is essential reading.Bitcoin, the first successful decentralized digital currency, is still in its infancy and it's already spawned a multi-billion dollar global economy. This economy is open to anyone with the knowledge and passion to participate. Mastering Bitcoin provides you with the knowledge you need (passion not included).This book includes:A broad introduction to bitcoin--ideal for non-technical users, investors, and business executivesAn explanation of the technical foundations of bitcoin and cryptographic currencies for developers, engineers, and software and systems architectsDetails of the bitcoin decentralized network, peer-to-peer architecture, transaction lifecycle, and security principlesOffshoots of the bitcoin and blockchain inventions, including alternative chains, currencies, and applicationsUser stories, analogies, examples, and code snippets illustrating key technical concepts
The Book of PoC||GTFO
Manul Laphroaig - 2017
Until now, the journal has only been available online or printed and distributed for free at hacker conferences worldwide.Consistent with the journal's quirky, biblical style, this book comes with all the trimmings: a leatherette cover, ribbon bookmark, bible paper, and gilt-edged pages. The book features more than 80 technical essays from numerous famous hackers, authors of classics like "Reliable Code Execution on a Tamagotchi," "ELFs are Dorky, Elves are Cool," "Burning a Phone," "Forget Not the Humble Timing Attack," and "A Sermon on Hacker Privilege." Twenty-four full-color pages by Ange Albertini illustrate many of the clever tricks described in the text.
Clojure for the Brave and True
Daniel Higginbotham - 2015
At long last you'll be united with the programming language you've been longing for: Clojure!As a Lisp-style functional programming language, Clojure lets you write robust and elegant code, and because it runs on the Java Virtual Machine, you can take advantage of the vast Java ecosystem. Clojure for the Brave and True offers a "dessert-first" approach: you'll start playing with real programs immediately, as you steadily acclimate to the abstract but powerful features of Lisp and functional programming. Inside you'll find an offbeat, practical guide to Clojure, filled with quirky sample programs that catch cheese thieves and track glittery vampires.Learn how to: Wield Clojure's core functions Use Emacs for Clojure development Write macros to modify Clojure itself Use Clojure's tools to simplify concurrency and parallel programmingClojure for the Brave and True assumes no prior experience with Clojure, the Java Virtual Machine, or functional programming. Are you ready, brave reader, to meet your true destiny? Grab your best pair of parentheses—you're about to embark on an epic journey into the world of Clojure!
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.
Machine Learning for Absolute Beginners
Oliver Theobald - 2017
The manner in which computers are now able to mimic human thinking is rapidly exceeding human capabilities in everything from chess to picking the winner of a song contest. In the age of machine learning, computers do not strictly need to receive an ‘input command’ to perform a task, but rather ‘input data’. From the input of data they are able to form their own decisions and take actions virtually as a human would. But as a machine, can consider many more scenarios and execute calculations to solve complex problems. This is the element that excites companies and budding machine learning engineers the most. The ability to solve complex problems never before attempted. This is also perhaps one reason why you are looking at purchasing this book, to gain a beginner's introduction to machine learning. This book provides a plain English introduction to the following topics: - Artificial Intelligence - Big Data - Downloading Free Datasets - Regression - Support Vector Machine Algorithms - Deep Learning/Neural Networks - Data Reduction - Clustering - Association Analysis - Decision Trees - Recommenders - Machine Learning Careers This book has recently been updated following feedback from readers. Version II now includes: - New Chapter: Decision Trees - Cleanup of minor errors
A Theory of Fun for Game Design
Raph Koster - 2004
It features a novel way of teaching interactive designers how to create and improve their designs to incorporate the highest degree of fun. As the book shows, designing for fun is all about making interactive products like games highly entertaining, engaging, and addictive. The book's unique approach of providing a highly visual storyboard approach combined with a narrative on the art and practice of designing for fun is sure to be a hit with game and interactive designers.At first glance A Theory of Fun for Game Design is a book that will truly inspire and challenge game designers to think in new ways; however, its universal message will influence designers from all walks of life. This book captures the real essence of what drives us to seek out products and experiences that are truly fun and entertaining. The author masterfully presents his engaging theory by showing readers how many designs are lacking because they are predictable and not engaging enough. He then explains how great designers use different types of elements in new ways to make designs more fun and compelling. Anyone who is interested in design will enjoy how the book works on two levels--as a quick inspiration guide to game design, or as an informative discussion that details the insightful thinking from a great mind in the game industry.
Natural Language Processing with Python
Steven Bird - 2009
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.
Spark: The Definitive Guide: Big Data Processing Made Simple
Bill Chambers - 2018
With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals.
You’ll explore the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library.
Get a gentle overview of big data and Spark
Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples
Dive into Spark’s low-level APIs, RDDs, and execution of SQL and DataFrames
Understand how Spark runs on a cluster
Debug, monitor, and tune Spark clusters and applications
Learn the power of Structured Streaming, Spark’s stream-processing engine
Learn how you can apply MLlib to a variety of problems, including classification or recommendation
The C# Programming Yellow Book
Rob Miles - 2010
With jokes, puns, and a rigorous problem solving based approach. You can download all the code samples used in the book from here: http://www.robmiles.com/s/Yellow-Book...