The Feel Of Algorithms
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The Feel Of Algorithms
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Author : Minna Ruckenstein
language : en
Publisher: Univ of California Press
Release Date : 2023-05-23
The Feel Of Algorithms written by Minna Ruckenstein and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-23 with categories.
Why do we feel excited, afraid, and frustrated by algorithms? The Feel of Algorithms brings relatable first-person accounts of what it means to experience algorithms emotionally alongside interdisciplinary social science research, to reveal how political and economic processes are felt in the everyday. People's algorithm stories might fail to separate fact and misconception, and circulate wishful, erroneous, or fearful views of digital technologies. Yet rather than treating algorithmic folklore as evidence of ignorance, this novel book explains why personal anecdotes are an important source of algorithmic knowledge. Minna Ruckenstein argues that we get to know algorithms by feeling their actions and telling stories about them. The Feel of Algorithms shows how taking everyday algorithmic emotions seriously would balances the current discussion, which has a tendency to draw conclusions based on celebratory or oppositional responses to imagined future effects. An everyday focus zooms into experiences of pleasure, fear, and irritation, highlighting how political aims and ethical tensions play out in visions, practices, and emotional responses. This book shows that feelings aid in recognizing troubling practices, and also calls for alternatives that are currently ignored or suppressed.
Introduction To Algorithms Third Edition
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Author : Thomas H. Cormen
language : en
Publisher: MIT Press
Release Date : 2009-07-31
Introduction To Algorithms Third Edition written by Thomas H. Cormen and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-31 with Computers categories.
The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.
The Algorithm Design Manual
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Author : Steven S Skiena
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-05
The Algorithm Design Manual written by Steven S Skiena and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-05 with Computers categories.
This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: • Doubles the tutorial material and exercises over the first edition • Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video • Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them • Includes several NEW "war stories" relating experiences from real-world applications • Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java
Algorithms For Dummies
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Author : John Paul Mueller
language : en
Publisher: John Wiley & Sons
Release Date : 2022-05-03
Algorithms For Dummies written by John Paul Mueller and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-03 with Computers categories.
Your secret weapon to understanding—and using!—one of the most powerful influences in the world today From your Facebook News Feed to your most recent insurance premiums—even making toast!—algorithms play a role in virtually everything that happens in modern society and in your personal life. And while they can seem complicated from a distance, the reality is that, with a little help, anyone can understand—and even use—these powerful problem-solving tools! In Algorithms For Dummies, you'll discover the basics of algorithms, including what they are, how they work, where you can find them (spoiler alert: everywhere!), who invented the most important ones in use today (a Greek philosopher is involved), and how to create them yourself. You'll also find: Dozens of graphs and charts that help you understand the inner workings of algorithms Links to an online repository called GitHub for constant access to updated code Step-by-step instructions on how to use Google Colaboratory, a zero-setup coding environment that runs right from your browser Whether you're a curious internet user wondering how Google seems to always know the right answer to your question or a beginning computer science student looking for a head start on your next class, Algorithms For Dummies is the can't-miss resource you've been waiting for.
Mastering Machine Learning Algorithms
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Author : Giuseppe Bonaccorso
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-25
Mastering Machine Learning Algorithms written by Giuseppe Bonaccorso and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-25 with Computers categories.
Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and more Book Description Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learn Explore how a ML model can be trained, optimized, and evaluated Understand how to create and learn static and dynamic probabilistic models Successfully cluster high-dimensional data and evaluate model accuracy Discover how artificial neural networks work and how to train, optimize, and validate them Work with Autoencoders and Generative Adversarial Networks Apply label spreading and propagation to large datasets Explore the most important Reinforcement Learning techniques Who this book is for This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide.
Thinking In Algorithms
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Author : Albert Rutherford
language : en
Publisher:
Release Date : 2021
Thinking In Algorithms written by Albert Rutherford and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Algorithms categories.
Algorithms
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Author : Jeff Erickson
language : en
Publisher:
Release Date : 2019-06-13
Algorithms written by Jeff Erickson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-13 with categories.
Algorithms are the lifeblood of computer science. They are the machines that proofs build and the music that programs play. Their history is as old as mathematics itself. This textbook is a wide-ranging, idiosyncratic treatise on the design and analysis of algorithms, covering several fundamental techniques, with an emphasis on intuition and the problem-solving process. The book includes important classical examples, hundreds of battle-tested exercises, far too many historical digressions, and exaclty four typos. Jeff Erickson is a computer science professor at the University of Illinois, Urbana-Champaign; this book is based on algorithms classes he has taught there since 1998.
Python Algorithms
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Author : Magnus Lie Hetland
language : en
Publisher: Apress
Release Date : 2011-02-27
Python Algorithms written by Magnus Lie Hetland and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-27 with Computers categories.
Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.
Hello World
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Author : Hannah Fry
language : en
Publisher: Random House
Release Date : 2018-09-06
Hello World written by Hannah Fry and has been published by Random House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-06 with Science categories.
'One of the best books yet written on data and algorithms. . .deserves a place on the bestseller charts.' (The Times) You are accused of a crime. Who would you rather determined your fate - a human or an algorithm? An algorithm is more consistent and less prone to error of judgement. Yet a human can look you in the eye before passing sentence. Welcome to the age of the algorithm, the story of a not-too-distant future where machines rule supreme, making important decisions - in healthcare, transport, finance, security, what we watch, where we go even who we send to prison. So how much should we rely on them? What kind of future do we want? Hannah Fry takes us on a tour of the good, the bad and the downright ugly of the algorithms that surround us. In Hello World she lifts the lid on their inner workings, demonstrates their power, exposes their limitations, and examines whether they really are an improvement on the humans they are replacing. A BBC RADIO 4: BOOK OF THE WEEK SHORTLISTED FOR THE 2018 BAILLIE GIFFORD PRIZE AND 2018 ROYAL SOCIETY SCIENCE BOOK PRIZE
Outnumbered
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Author : David Sumpter
language : en
Publisher: Bloomsbury Publishing
Release Date : 2018-04-19
Outnumbered written by David Sumpter and has been published by Bloomsbury Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-19 with Computers categories.
'Fascinating' Financial Times Algorithms are running our society, and as the Cambridge Analytica story has revealed, we don't really know what they are up to. Our increasing reliance on technology and the internet has opened a window for mathematicians and data researchers to gaze through into our lives. Using the data they are constantly collecting about where we travel, where we shop, what we buy and what interests us, they can begin to predict our daily habits. But how reliable is this data? Without understanding what mathematics can and can't do, it is impossible to get a handle on how it is changing our lives. In this book, David Sumpter takes an algorithm-strewn journey to the dark side of mathematics. He investigates the equations that analyse us, influence us and will (maybe) become like us, answering questions such as: Who are Cambridge Analytica? And what are they doing with our data? How does Facebook build a 100-dimensional picture of your personality? Are Google algorithms racist and sexist? Why do election predictions fail so drastically? Are algorithms that are designed to find criminals making terrible mistakes? What does the future hold as we relinquish our decision-making to machines? Featuring interviews with those working at the cutting edge of algorithm research, including Alex Kogan from the Cambridge Analytica story, along with a healthy dose of mathematical self-experiment, Outnumbered will explain how mathematics and statistics work in the real world, and what we should and shouldn't worry about. A lot of people feel outnumbered by algorithms – don't be one of them.