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

    In Override, Caroline Williams goes on a mission to find out.Neuroplasticity dictates that the brain adapts physically as we learn something new. But although brain training may be all the rage, the latest studies indicate that it doesn't actually do much to make you smarter. So what does?Visiting top neuroscientists in their labs, Williams volunteers herself as a guinea pig, challenging researchers to make real changes to her imperfect brain. She seeks to improve on weaknesses such as her limited attention span and tendency to worry too much, and then branches out into more mysterious areas such as intelligence, creativity, and the perception of time.Trying everything from high-tech brain stimulation to meditation, adding bolt-on senses and retraining her stress response, Override is an intimate, fascinating journey into discovering what neuroscience can really do for us.

    With Java 5.0, you'll not only find substantial changes in the platform, but to the language itself-something that developers of Java took five years to complete. The main goal of Java 5.0 is to make it easier for you to develop safe, powerful code, but none of these improvements makes Java any easier to learn, even if you've programmed with Java for years. And that means our bestselling hands-on tutorial takes on even greater significance."Learning Java" is the most widely sought introduction to the programming language that's changed the way we think about computing. Our updated third edition takes an objective, no-nonsense approach to the new features in Java 5.0, some of which are drastically different from the way things were done in any previous versions. The most essential change is the addition of "generics," a feature that allows developers to write, test, and deploy code once, and then reuse the code again and again for different data types. The beauty of generics is that more problems will be caught during development, and "Learning Java" will show you exactly how it's done.Java 5.0 also adds more than 1,000 new classes to the Java library. That means 1,000 new things you can do without having to program it in yourself. That's a huge change. With our book's practical examples, you'll come up to speed quickly on this and other new features such as loops and threads. The new edition also includes an introduction to Eclipse, the open source IDE that is growing in popularity. "Learning Java," 3rd Edition addresses all of the important uses of Java, such as web applications, servlets, and XML that are increasingly driving enterprise applications.

    Watson Sr. and his son, Thomas J. Watson Jr., together built the international colossus that is IBM. This is their story: a riveting and revealing account of two men who loved each other--and fought each other--with a terrible fierceness.But along with the story of a father and son, this is IBM's story too. It chronicles the management insights that shaped its course and its unique corporate culture, the style that made Thomas Watson Sr. one of America's most charismatic bosses, and the daring decisions by Thomas Watson Jr. that transformed IBM into the world's largest computing company. One of the greatest business-success stories of all time, Father, Son & Co. is a moving lesson for fathers who dream for their children, as well as a testament to American ingenuity and values, told in a disarmingly frank and eloquent voice.Promising to remain an important business reference as we move into the next century, FATHER, SON & CO. takes a look at the management insight that helped to shape IBM's course and unique corporate culture.  It looks at Watson, Sr., one of America's most charismatic bosses, and Watson, Jr., who spurred IBM into the computer age.Ten years after its original publication, FATHER, SON & CO. remains a uniquely honest book. Watson's willingness to write about the loving but ferociously combative relationship he had with his father and the turbulent battles behind some of IBM's most far-reaching decisions gives readers rare insights into the realities of leadership. -->

    '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.

    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

    Thalia Bourdette. Thalia’s name is a lie as much as her past. If her truth is revealed, she and her young daughter will be in mortal danger.Only two people know the truth about Thalia – the sheriff and the outlaw Willsby. To protect her, the sheriff sets out to hunt a killer who refuses to die.Enjoy this new classic Western from Sam Scott. Men of honor, outlaws, and a touch of romance.

    Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks.Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data--or anything in between--this guide makes it easier to understand and implement machine learning seamlessly.Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!

     “Deeply reported and bracingly written, this book is an indispensable guide to modern innovation and entrepreneurship.” —Walter Isaacson, New York Times bestselling author of Code BreakerToday, PayPal’s founders and earliest employees are considered the technology industry’s most powerful network. Since leaving PayPal, they have formed, funded, and advised the leading companies of our era, including Tesla, Facebook, YouTube, SpaceX, Yelp, Palantir, and LinkedIn, among many others. As a group, they have driven twenty-first-century innovation and entrepreneurship. Their names stir passions; they’re as controversial as they are admired. Yet for all their influence, the story of where they first started has gone largely untold. Before igniting the commercial space race or jumpstarting social media’s rise, they were the unknown creators of a scrappy online payments start-up called PayPal. In building what became one of the world’s foremost companies, they faced bruising competition, internal strife, the emergence of widespread online fraud, and the devastating dot-com bust of the 2000s. Their success was anything but certain. In The Founders: The Story of PayPal and the Entrepreneurs Who Shaped Silicon Valley, award-winning author and biographer Jimmy Soni explores PayPal’s turbulent early days. With hundreds of interviews and unprecedented access to thousands of pages of internal material, he shows how the seeds of so much of what shapes our world today—fast-scaling digital start-ups, cashless currency concepts, mobile money transfer—were planted two decades ago. He also reveals the stories of countless individuals who were left out of the front-page features and banner headlines but who were central to PayPal’s success. Described as “an intensely magnetic chronicle” (The New York Times) and “engrossing” (Business Insider), The Founders is a story of iteration and inventiveness—the products of which have cast a long and powerful shadow over modern life. This narrative illustrates how this rare assemblage of talent came to work together and how their collaboration changed our world forever.

    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.

    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.

    Technological advances in fields as diverse as quantum mechanics, electronics, and nanotechnology are proving increasingly important to city life, and the urban world will turn to science to deliver solutions to the problems of the future; more than 50 percent of the world's population now lives in cities, and that proportion is growing fast. Can engineering provide the answer to a viable megacity future?SCIENCE AND THE CITY starts at your front door and guides you through the technology of everyday city life: how new approaches to building materials help to construct the tallest skyscrapers in Dubai, how New Yorkers use light to treat their drinking water, how Tokyo commuters' footsteps power gates in train stations. Uncovering the science and engineering that shapes our cities, Laurie Winkless reveals how technology will help us meet the challenges of a soaring world population--from an ever-increasing demand for power, water, and internet access, to simply how to get about in a megacity of tens of millions of people. Laurie Winkless is a physicist with an undergraduate degree from Trinity College, Dublin, and a master's degree in space science from University College London. She has worked at the National Physical Laboratory, specializing in functional materials and is an expert on thermoelectric energy harvesting, which involves using material science to capture and convert waste heat into electricity. This is her first book, written while living in her favorite city, London.

    There can be so much information available that you can't even decide where to start. Or worse, you start down the path of learning and quickly discover too many concepts, commands, and nuances that aren't explained. This kind of experience is frustrating and leaves you with more questions than answers.Python Programming for Beginners doesn't make any assumptions about your background or knowledge of Python or computer programming. You need no prior knowledge to benefit from this book. You will be guided step by step using a logical and systematic approach. As new concepts, commands, or jargon are encountered they are explained in plain language, making it easy for anyone to understand. Here is what you will learn by reading Python Programming for Beginners: When to use Python 2 and when to use Python 3. How to install Python on Windows, Mac, and Linux. Screenshots included. How to prepare your computer for programming in Python. The various ways to run a Python program on Windows, Mac, and Linux. Suggested text editors and integrated development environments to use when coding in Python. How to work with various data types including strings, lists, tuples, dictionaries, booleans, and more. What variables are and when to use them. How to perform mathematical operations using Python. How to capture input from a user. Ways to control the flow of your programs. The importance of white space in Python. How to organize your Python programs -- Learn what goes where. What modules are, when you should use them, and how to create your own. How to define and use functions. Important built-in Python functions that you'll use often. How to read from and write to files. The difference between binary and text files. Various ways of getting help and find Python documentation. Much more... Every single code example in the book is available to download, providing you with all the Python code you need at your fingertips! Scroll up, click the Buy Now With 1 Click button and get started learning Python today!

    It examines emerging trends and developments in society, technology, economy, and business, and makes educated speculations as to where they might take us.

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data