Book picks similar to
Mechanizing Proof: Computing, Risk, and Trust by Donald Angus MacKenzie
computer-science
history
tech
ph-d-program-reading
The New New Thing: A Silicon Valley Story
Michael Lewis - 1999
He found this in Jim Clark, a man whose achievements include the founding of three separate billion-dollar companies. Lewis also found much more, and the result—the best-selling book The New New Thing—is an ingeniously conceived history of the Internet revolution.
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.
PI in the Sky: Counting, Thinking, and Being
John D. Barrow - 1992
Barrow's Pi in the Sky is a profound -- and profoundly different -- exploration of the world of mathematics: where it comes from, what it is, and where it's going to take us if we follow it to the limit in our search for the ultimate meaning of the universe. Barrow begins by investigating whether math is a purely human invention inspired by our practical needs. Or is it something inherent in nature waiting to be discovered?In answering these questions, Barrow provides a bridge between the usually irreconcilable worlds of mathematics and theology. Along the way, he treats us to a history of counting all over the world, from Egyptian hieroglyphics to logical friction, from number mysticism to Marxist mathematics. And he introduces us to a host of peculiar individuals who have thought some of the deepest and strangest thoughts that human minds have ever thought, from Lao-Tse to Robert Pirsig, Charles Darwin, and Umberto Eco. Barrow thus provides the historical framework and the intellectual tools necessary to an understanding of some of today's weightiest mathematical concepts.
OS X 10.10 Yosemite: The Ars Technica Review
John Siracusa - 2014
Siracusa's overview, wrap-up, and critique of everything new in OS X 10.10 Yosemite.
The Google Story: Inside the Hottest Business, Media and Technology Success of Our Time
David A. Vise - 2005
The Google Story takes you deep inside the company's wild ride from an idea that struggled for funding in 1998 to a firm that rakes in billions in profits, making Brin and Page the wealthiest young men in America. Based on scrupulous research and extraordinary access to Google, this fast-moving narrative reveals how an unorthodox management style and culture of innovation enabled a search engine to shake up Madison Avenue and Wall Street, scoop up YouTube, and battle Microsoft at every turn. Not afraid of controversy, Google is expanding in Communist China and quietly working on a searchable genetic database, initiatives that test the founders' guiding mantra: DON'T BE EVIL.
Data Analysis with Open Source Tools: A Hands-On Guide for Programmers and Data Scientists
Philipp K. Janert - 2010
With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora
An Introduction to Statistical Learning: With Applications in R
Gareth James - 2013
This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
The Big Switch: Rewiring the World, from Edison to Google
Nicholas Carr - 2008
In a new chapter for this edition that brings the story up-to-date, Nicholas Carr revisits the dramatic new world being conjured from the circuits of the "World Wide Computer."
The Design of Design: Essays from a Computer Scientist
Frederick P. Brooks Jr. - 2010
But what do we really know about the design process? What leads to effective, elegant designs? The Design of Design addresses these questions. These new essays by Fred Brooks contain extraordinary insights for designers in every discipline. Brooks pinpoints constants inherent in all design projects and uncovers processes and patterns likely to lead to excellence. Drawing on conversations with dozens of exceptional designers, as well as his own experiences in several design domains, Brooks observes that bold design decisions lead to better outcomes. The author tracks the evolution of the design process, treats collaborative and distributed design, and illuminates what makes a truly great designer. He examines the nuts and bolts of design processes, including budget constraints of many kinds, aesthetics, design empiricism, and tools, and grounds this discussion in his own real-world examples--case studies ranging from home construction to IBM's Operating System/360. Throughout, Brooks reveals keys to success that every designer, design project manager, and design researcher should know.
Race After Technology: Abolitionist Tools for the New Jim Code
Ruha Benjamin - 2019
Presenting the concept of the "New Jim Code," she shows how a range of discriminatory designs encode inequity by explicitly amplifying racial hierarchies; by ignoring but thereby replicating social divisions; or by aiming to fix racial bias but ultimately doing quite the opposite. Moreover, she makes a compelling case for race itself as a kind of technology, designed to stratify and sanctify social injustice in the architecture of everyday life.This illuminating guide provides conceptual tools for decoding tech promises with sociologically informed skepticism. In doing so, it challenges us to question not only the technologies we are sold but also the ones we ourselves manufacture.If you adopt this book for classroom use in the 2019-2020 academic year, the author would be pleased to arrange to Skype to a session of your class. If interested, enter your details in this sign-up sheet https: //buff.ly/2wJsvZr
Programming the Universe: A Quantum Computer Scientist Takes on the Cosmos
Seth Lloyd - 2006
This wonderfully accessible book illuminates the professional and personal paths that led him to this remarkable conclusion.All interactions between particles in the universe, Lloyd explains, convey not only energy but also information—in other words, particles not only collide, they compute. And what is the entire universe computing, ultimately? “Its own dynamical evolution,” he says. “As the computation proceeds, reality unfolds.”To elucidate his theory, Lloyd examines the history of the cosmos, posing questions that in other hands might seem unfathomably complex: How much information is there in the universe? What information existed at the moment of the Big Bang and what happened to it? How do quantum mechanics and chaos theory interact to create our world? Could we attempt to re-create it on a giant quantum computer? Programming the Universe presents an original and compelling vision of reality, revealing our world in an entirely new light.
Eloquent JavaScript: A Modern Introduction to Programming
Marijn Haverbeke - 2010
I loved the tutorial-style game-like program development. This book rekindled my earliest joys of programming. Plus, JavaScript!" —Brendan Eich, creator of JavaScriptJavaScript is the language of the Web, and it's at the heart of every modern website from the lowliest personal blog to the mighty Google Apps. Though it's simple for beginners to pick up and play with, JavaScript is not a toy—it's a flexible and complex language, capable of much more than the showy tricks most programmers use it for.Eloquent JavaScript goes beyond the cut-and-paste scripts of the recipe books and teaches you to write code that's elegant and effective. You'll start with the basics of programming, and learn to use variables, control structures, functions, and data structures. Then you'll dive into the real JavaScript artistry: higher-order functions, closures, and object-oriented programming.Along the way you'll learn to:Master basic programming techniques and best practices Harness the power of functional and object-oriented programming Use regular expressions to quickly parse and manipulate strings Gracefully deal with errors and browser incompatibilities Handle browser events and alter the DOM structure Most importantly, Eloquent JavaScript will teach you to express yourself in code with precision and beauty. After all, great programming is an art, not a science—so why settle for a killer app when you can create a masterpiece?
Python Data Science Handbook: Tools and Techniques for Developers
Jake Vanderplas - 2016
Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Out of the Ether: The Amazing Story of Ethereum and the $55 Million Heist that Almost Destroyed It All
Matthew Leising - 2020
It also chronicles the creation of the Ethereum blockchain from the mind of inventor Vitalik Buterin to the ragtag group of people he assembled around him to build the second-largest crypto universe after Bitcoin.Celebrated journalist and author Matthew Leising tells the full story of one of the most incredible chapters in cryptocurrency history. He covers the aftermath of the heist as well, explaining the extreme lengths the victims of the theft and the creators of Ethereum went to in order to try and limit the damage. The book covers:The creation of EthereumAn explanation of the nature of blockchain and cryptocurrencyThe activities of a colorful cast of hackers, coders, investors, and thievesPerfect for anyone with even a passing interest in the world of modern fintech or daring electronic heists, Out of the Ether is a story of genius and greed that’s so incredible you may just choose not to believe it.
Selfie: How We Became So Self-Obsessed and What It's Doing to Us
Will Storr - 2017
This is our culture’s image of the perfect self. We see this person everywhere: in advertising, in the press, all over social media. We’re told that to be this person you just have to follow your dreams, that our potential is limitless, that we are the source of our own success. But this model of the perfect self can be extremely dangerous. People are suffering under the torture of this impossible fantasy. Unprecedented social pressure is leading to increases in depression and suicide. Where does this ideal come from? Why is it so powerful? Is there any way to break its spell? To answer these questions, Selfie by Will Storr takes us from the shores of Ancient Greece, through the Christian Middle Ages, to the self-esteem evangelists of 1980s California, the rise of narcissism and the selfie generation, and right up to the era of hyper-individualistic neoliberalism in which we live now. It tells the extraordinary story of the person we all know so intimately – our self.