Book picks similar to
Mastering Reinforcement Learning with Python: Build next-generation, self-learning models using reinforcement learning techniques and best practices by Enes Bilgin
artificial-intelligence
reinforcement-learning
tb-data
technical
The Business of Platforms: Strategy in the Age of Digital Competition, Innovation, and Power
Michael A. Cusumano - 2019
Managers and entrepreneurs in the digital era must learn to live in two worlds—the conventional economy and the platform economy. Platforms that operate for business purposes usually exist at the level of an industry or ecosystem, bringing together individuals and organizations so they can innovate and interact in ways not otherwise possible. Platforms create economic value far beyond what we see in conventional companies.The Business of Platforms is an invaluable, in-depth look at platform strategy and digital innovation. Cusumano, Gawer, and Yoffie address how a small number of companies have come to exert extraordinary influence over every dimension of our personal, professional, and political lives. They explain how these new entities differ from the powerful corporations of the past. They also question whether there are limits to the market dominance and expansion of these digital juggernauts. Finally, they discuss the role governments should play in rethinking data privacy laws, antitrust, and other regulations that could reign in abuses from these powerful businesses.Their goal is to help managers and entrepreneurs build platform businesses that can stand the test of time and win their share of battles with both digital and conventional competitors. As experts who have studied and worked with these firms for some thirty years, this book is the most authoritative and timely investigation yet of the powerful economic and technological forces that make platform businesses, from Amazon and Apple to Microsoft, Facebook, and Google—all dominant players in shaping the global economy, the future of work, and the political world we now face.
Firing A Rocket : Stories of the Development of the Rocket Engines for the Saturn Launch Vehicles and the Lunar Module as Viewed from the Trenches (Kindle Single)
James R. French - 2017
But Neil Armstrong and Sally Ride would have never made history, and humankind would not have touched the stars, if not for the men and women on the ground who lit the fuse that launched the first rockets.Enthralled as a boy by the exploits of Flash Gordon and the novels of Robert Heinlein and Arthur C. Clarke—who put the science in science fiction—James French became one of the original unsung engineers of America’s groundbreaking space program. His fascinating memoir offers an up-close-and-technical look at building, testing, and perfecting the pioneering Saturn rockets and original lunar landing module, and he shares true tales, both humorous and harrowing, of life—and near death—on the front lines of scientific exploration.If you’ve ever said, “It’s not rocket science,” you’re right. It’s rocket engineering—and here’s your chance to marvel at how it changed the world and made it possible to explore all that lies beyond Earth. James R French graduated from MIT in 1958 with a degree of BSME Specializing in Propulsion. His first job was with Rocketdyne Division of North American Aviation where he worked on developmental testing of H-1 engines and combustion devices hardware for F-1 and J-2 engines used in Saturn 5. Mr. French has also worked at TRW Systems, where he was Lead Development Test Engineer on the Lunar Module Descent Engine, and Jet Propulsion Laboratory where he was Advanced Planetary studies Manager as well as Chief Engineer for the SP-100 Space Nuclear Power System and worked on Mariners 5, 6, 7, 8, and 9; Viking 1 & 2 and Voyager 1 & 2. . In 1986, he helped found American Rocket Co., a commercial launch company.Since 1987, Mr. French has been consultant to a variety of aerospace companies, SDIO, NASA, and USAF. He has participated in various startup companies in the private space flight arena and currently consults extensively to Blue Origin. Mr. French is co-author with Dr. Michael Griffin of the best-selling text Space Vehicle Design, published by AIAA. The second edition of the book has received the Summerfield Book Award for 2008. Mr. French is a Fellow of both AIAA and the British Interplanetary Society and a 50+ year member of AIAA. He has held several Technical Committee and other posts in AIAA. Cover design by Evan Twohy
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
Computer Age Statistical Inference: Algorithms, Evidence, and Data Science
Bradley Efron - 2016
'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
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.
The Hundred-Page Machine Learning Book
Andriy Burkov - 2019
During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.
Machine Learning: A Probabilistic Perspective
Kevin P. Murphy - 2012
Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
Effective Python: 90 Specific Ways to Write Better Python (Effective Software Development Series)
Brett Slatkin - 2019
However, Python’s unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up. This second edition of Effective Python will help you master a truly “Pythonic” approach to programming, harnessing Python’s full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers’ best-selling Effective C++, Brett Slatkin brings together 90 Python best practices, tips, and shortcuts, and explains them with realistic code examples so that you can embrace Python with confidence. Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance. You’ll understand the best way to accomplish key tasks so you can write code that’s easier to understand, maintain, and improve. In addition to even more advice, this new edition substantially revises all items from the first edition to reflect how best practices have evolved. Key features include 30 new actionable guidelines for all major areas of Python Detailed explanations and examples of statements, expressions, and built-in types Best practices for writing functions that clarify intention, promote reuse, and avoid bugs Better techniques and idioms for using comprehensions and generator functions Coverage of how to accurately express behaviors with classes and interfaces Guidance on how to avoid pitfalls with metaclasses and dynamic attributes More efficient and clear approaches to concurrency and parallelism Solutions for optimizing and hardening to maximize performance and quality Techniques and built-in modules that aid in debugging and testing Tools and best practices for collaborative development Effective Python will prepare growing programmers to make a big impact using Python.
Game Programming Gems
Mark DeLoura - 2000
But instead of spending hours and hours trying to develop your own answers, now you can find out how the pros do it! Game Programming Gems is a hands-on, comprehensive resource packed with a variety of game programming algorithms written by experts from the game industry and edited by Mark DeLoura, former software engineering lead for Nintendo of America, Inc. and now the newly appointed editor-in-chief of Game Developer magazine. From animation and artificial intelligence to Z-buffering, lighting calculations, weather effects, curved surfaces, mutliple layer Internet gaming, to music and sound effects, all of the major techniques needed to develop a competitive game engine are covered. Game Programming Gems is written in a style accessible to individuals with a range of expertise levels. All of the source code for each algorithm is included and can be used by advanced programmers immediately. For aspiring programmers, there is a detailed tutorial to work through before attempting the code, and suggestions for possible modifications and optimizations are included as well.
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.
Machine Learning Yearning
Andrew Ng
But building a machine learning system requires that you make practical decisions: Should you collect more training data? Should you use end-to-end deep learning? How do you deal with your training set not matching your test set? and many more. Historically, the only way to learn how to make these "strategy" decisions has been a multi-year apprenticeship in a graduate program or company. This is a book to help you quickly gain this skill, so that you can become better at building AI systems.
The Options Playbook: Featuring 40 strategies for bulls, bears, rookies, all-stars and everyone in between.
Brian Overby - 2009
No confusing jargon. No unnecessary mumbo-jumbo. Just clear, easy-to-understand explanations of more than 40 of the most popular option strategies broken down into a play-by-play format including: Play Name: Long Call, Short Call Spread, Iron Condor, etc. The Setup: The goals and reasons to run each play Who Should Run It: Rookies, Veterans or All-Stars, based on degree of difficulty When To Run It: Describes each play as bullish, bearish or neutral The Strategy: A detailed overview of each strategy, their risks and the specific costs associated with multi-leg strategies. description For the first-time option trader The Options Playbook features a "Rookie's Corner," addressing the basic definitions and concepts you need to understand this market, tips to avoid common beginner's mistakes, and suggested strategies to "get your feet wet." For more experienced option traders, an expanded section on implied volatility explains how this handy variable can be used to find the potential range of the stock over the options life. A detailed section on pricing variables (Greeks) helps you understand how an option's price is affected by changes in market conditions. You will also learn how time decay and a change in implied volatility can affect your trade after it's in place and how to recover if things don't go according to plan. The Options Playbook features Options Guy Tips from TradeKing Senior Analyst Brian Overby. Like any good coach, Overby's handy insights help you put theory into successful real-world trading. This expanded 2nd edition includes 10 new plays and 56 new pages of handy content describing a brief history of options, five common mistakes options traders make and how to avoid them, an expanded glossary, how to manage option positions by rolling to a different month and strike, to explaining the difference between index and stock options, managing early exercise and assignment and how to calculate position delta and use it to manage overall position risk of a multi-leg option strategy. Options involve risk and are not suitable for all investors. It is possible to lose more money than invested. Before making any investment decisions, please read Characteristics and Risks of Standardized Options that accompanies The Options Playbook and available at: tradeking.com/ODD. (c) 2015 TradeKing Group, Inc. All rights reserved. Securities offered through TradeKing, LLC, member FINRA and SIPC.
The Fourth Transformation: How Augmented Reality and Artificial Intelligence Change Everything
Robert Scoble - 2016
Artificial Intelligence
Patrick Henry Winston - 1977
From the book, you learn why the field is important, both as a branch of engineering and as a science. If you are a computer scientist or an engineer, you will enjoy the book, because it provides a cornucopia of new ideas for representing knowledge, using knowledge, and building practical systems. If you are a psychologist, biologist, linguist, or philosopher, you will enjoy the book because it provides an exciting computational perspective on the mystery of intelligence. The Knowledge You Need This completely rewritten and updated edition of Artificial Intelligence reflects the revolutionary progress made since the previous edition was published. Part I is about representing knowledge and about reasoning methods that make use of knowledge. The material covered includes the semantic-net family of representations, describe and match, generate and test, means-ends analysis, problem reduction, basic search, optimal search, adversarial search, rule chaining, the rete algorithm, frame inheritance, topological sorting, constraint propagation, logic, truth
Feynman Lectures On Computation
Richard P. Feynman - 1996
Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a “Feynmanesque” overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.