And considering that the "one man" is Neal Stephenson, "the hacker Hemingway" (Newsweek) -- acclaimed novelist, pragmatist, seer, nerd-friendly philosopher, and nationally bestselling author of groundbreaking literary works (Snow Crash, Cryptonomicon, etc., etc.) -- the word is well worth hearing. Mostly well-reasoned examination and partial rant, Stephenson's In the Beginning... was the Command Line is a thoughtful, irreverent, hilarious treatise on the cyber-culture past and present; on operating system tyrannies and downloaded popular revolutions; on the Internet, Disney World, Big Bangs, not to mention the meaning of life itself.

    The calculus is not a hard subject and I prove this through an easy to read and obvious approach spanning only 100 pages. I have written this book with the following type of student in mind; the non-traditional student returning to college after a long break, a notoriously weak student in math who just needs to get past calculus to obtain a degree, and the garage tinkerer who wishes to understand a little more about the technical subjects. This book is meant to address the many fundamental thought-blocks that keep the average 'mathaphobe' (or just an interested person who doesn't have the time to enroll in a course) from excelling in mathematics in a clear and concise manner. It is my sincerest hope that this book helps you with your needs.Show more Show less

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    He’s a sociopath. And your boss, teacher, and colleague? They may be sociopaths too.We are accustomed to think of sociopaths as violent criminals, but in The Sociopath Next Door, Harvard psychologist Martha Stout reveals that a shocking 4 percent of ordinary people—one in twenty-five—has an often undetected mental disorder, the chief symptom of which is that that person possesses no conscience. He or she has no ability whatsoever to feel shame, guilt, or remorse. One in twenty-five everyday Americans, therefore, is secretly a sociopath. They could be your colleague, your neighbor, even family. And they can do literally anything at all and feel absolutely no guilt. How do we recognize the remorseless? One of their chief characteristics is a kind of glow or charisma that makes sociopaths more charming or interesting than the other people around them. They’re more spontaneous, more intense, more complex, or even sexier than everyone else, making them tricky to identify and leaving us easily seduced. Fundamentally, sociopaths are different because they cannot love. Sociopaths learn early on to show sham emotion, but underneath they are indifferent to others’ suffering. They live to dominate and thrill to win. The fact is, we all almost certainly know at least one or more sociopaths already. Part of the urgency in reading The Sociopath Next Door is the moment when we suddenly recognize that someone we know—someone we worked for, or were involved with, or voted for—is a sociopath. But what do we do with that knowledge? To arm us against the sociopath, Dr. Stout teaches us to question authority, suspect flattery, and beware the pity play. Above all, she writes, when a sociopath is beckoning, do not join the game. It is the ruthless versus the rest of us, and The Sociopath Next Door will show you how to recognize and defeat the devil you know.

    In this one-of-a-kind text, author V. Anton Spraul breaks down the ways that programmers solve problems and teaches you what other introductory books often ignore: how to Think Like a Programmer. Each chapter tackles a single programming concept, like classes, pointers, and recursion, and open-ended exercises throughout challenge you to apply your knowledge. You'll also learn how to:Split problems into discrete components to make them easier to solve Make the most of code reuse with functions, classes, and libraries Pick the perfect data structure for a particular job Master more advanced programming tools like recursion and dynamic memory Organize your thoughts and develop strategies to tackle particular types of problems Although the book's examples are written in C++, the creative problem-solving concepts they illustrate go beyond any particular language; in fact, they often reach outside the realm of computer science. As the most skillful programmers know, writing great code is a creative art—and the first step in creating your masterpiece is learning to Think Like a Programmer.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    This is the undisputed go-to guide to Rust, written by two members of the Rust core team, with feedback and contributions from 42 members of the community. The book assumes that you’ve written code in another programming language but makes no assumptions about which one, meaning the material is accessible and useful to developers from a wide variety of programming backgrounds.Known by the Rust community as "The Book," The Rust Programming Language includes concept chapters, where you’ll learn about a particular aspect of Rust, and project chapters, where you’ll apply what you’ve learned so far to build small programs.The Book opens with a quick hands-on project to introduce the basics then explores key concepts in depth, such as ownership, the type system, error handling, and fearless concurrency. Next come detailed explanations of Rust-oriented perspectives on topics like pattern matching, iterators, and smart pointers, with concrete examples and exercises--taking you from theory to practice.The Rust Programming Language will show you how to: Grasp important concepts unique to Rust like ownership, borrowing, and lifetimes Use Cargo, Rust’s built-in package manager, to build and maintain your code, including downloading and building dependencies Effectively use Rust’s zero-cost abstractions and employ your ownYou’ll learn to develop reliable code that’s speed and memory efficient, while avoiding the infamous and arcane programming pitfalls common at the systems level. When you need to dive down into lower-level control, this guide will show you how without taking on the customary risk of crashes or security holes and without requiring you to learn the fine points of a fickle toolchain.You’ll also learn how to create command line programs, build single- and multithreaded web servers, and much more.The Rust Programming Language fully embraces Rust’s potential to empower its users. This friendly and approachable guide will help you build not only your knowledge of Rust but also your ability to program with confidence in a wider variety of domains.

    The term 'hacker' has been redefined to consist of anyone who has an insatiable curiosity as to how things work--and how they can try to make them better. This book is aimed at hackers of all skill levels and explains the classical principles and techniques behind beautiful designs by deconstructing those designs in order to understand what makes them so remarkable. Author and designer David Kadavy provides you with the framework for understanding good design and places a special emphasis on interactive mediums. You'll explore color theory, the role of proportion and geometry in design, and the relationship between medium and form. Packed with unique reverse engineering design examples, this book inspires and encourages you to discover and create new beauty in a variety of formats. Breaks down and studies the classical principles and techniques behind the creation of beautiful design. Illustrates cultural and contextual considerations in communicating to a specific audience. Discusses why design is important, the purpose of design, the various constraints of design, and how today's fonts are designed with the screen in mind. Dissects the elements of color, size, scale, proportion, medium, and form. Features a unique range of examples, including the graffiti in the ancient city of Pompeii, the lack of the color black in Monet's art, the style and sleekness of the iPhone, and more.By the end of this book, you'll be able to apply the featured design principles to your own web designs, mobile apps, or other digital work.

    Whether you're a beginner, and avid student, or an armchair expert, you'll find plenty to stimulate you within this book.--book jacket

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    Brian Greene, one of the world's leading string theorists, peels away the layers of mystery surrounding string theory to reveal a universe that consists of eleven dimensions, where the fabric of space tears and repairs itself, and all matter—from the smallest quarks to the most gargantuan supernovas—is generated by the vibrations of microscopically tiny loops of energy.Today physicists and mathematicians throughout the world are feverishly working on one of the most ambitious theories ever proposed: superstring theory. String theory, as it is often called, is the key to the Unified Field Theory that eluded Einstein for more than thirty years. Finally, the century-old antagonism between the large and the small-General Relativity and Quantum Theory-is resolved. String theory proclaims that all of the wondrous happenings in the universe, from the frantic dancing of subatomic quarks to the majestic swirling of heavenly galaxies, are reflections of one grand physical principle and manifestations of one single entity: microscopically tiny vibrating loops of energy, a billionth of a billionth the size of an atom. In this brilliantly articulated and refreshingly clear book, Greene relates the scientific story and the human struggle behind twentieth-century physics' search for a theory of everything.Through the masterful use of metaphor and analogy, The Elegant Universe makes some of the most sophisticated concepts ever contemplated viscerally accessible and thoroughly entertaining, bringing us closer than ever to understanding how the universe works.

    Now in book form for the first time, their simple method will teach you how to use basic design tools to create a life that will work for you.Using real-life stories and proven techniques like reframing, prototyping and mind-mapping, you will learn how to build your way forwards, step-by-positive-step, to a life that’s better by a design of your own making.Because a well-designed life means a life well-lived.

    Of course, it’s not all cooking; we’ll also run the New York and Chicago marathons, pay visits to Cinderella and Lewis Carroll, and even get to the bottom of a tomato’s identity as a vegetable. This is not the math of our high school classes: mathematics, Cheng shows us, is less about numbers and formulas and more about how we know, believe, and understand anything, including whether our brother took too much cake.At the heart of How to Bake Pi is Cheng’s work on category theory—a cutting-edge “mathematics of mathematics.” Cheng combines her theory work with her enthusiasm for cooking both to shed new light on the fundamentals of mathematics and to give readers a tour of a vast territory no popular book on math has explored before. Lively, funny, and clear, How to Bake Pi will dazzle the initiated while amusing and enlightening even the most hardened math-phobe.