It covers the basics of computer programming, including variables and values, functions, conditionals and control flow, program development and debugging. Later chapters cover basic algorithms and data structures.

    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.

    Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

    this is one of those rare books that will change your beliefs - and in doing so will change your life. tHE ANt AND tHE FERRARI offers readers a clear, navigable path through the big questions that confront us all today. What is the meaning of life? Can we be ethical beings in today's world? Can we know if there is life after death? Is there such a thing as Absolute truth? What caused the Big Bang and why should you care?

    Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video.With Beautiful Data, you will: Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web Learn how to visualize trends in urban crime, using maps and data mashups Discover the challenges of designing a data processing system that works within the constraints of space travel Learn how crowdsourcing and transparency have combined to advance the state of drug research Understand how new data can automatically trigger alerts when it matches or overlaps pre-existing data Learn about the massive infrastructure required to create, capture, and process DNA data That's only small sample of what you'll find in Beautiful Data. For anyone who handles data, this is a truly fascinating book. Contributors include:Nathan Yau Jonathan Follett and Matt Holm J.M. Hughes Raghu Ramakrishnan, Brian Cooper, and Utkarsh Srivastava Jeff Hammerbacher Jason Dykes and Jo Wood Jeff Jonas and Lisa Sokol Jud Valeski Alon Halevy and Jayant Madhavan Aaron Koblin with Valdean Klump Michal Migurski Jeff Heer Coco Krumme Peter Norvig Matt Wood and Ben Blackburne Jean-Claude Bradley, Rajarshi Guha, Andrew Lang, Pierre Lindenbaum, Cameron Neylon, Antony Williams, and Egon Willighagen Lukas Biewald and Brendan O'Connor Hadley Wickham, Deborah Swayne, and David Poole Andrew Gelman, Jonathan P. Kastellec, and Yair Ghitza Toby Segaran

    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

    It was the dawn of a new era in artificial intelligence: a machine capable of beating the reigning human champion at this most cerebral game. That moment was more than a century in the making, and in this breakthrough book, Kasparov reveals his astonishing side of the story for the first time. He describes how it felt to strategize against an implacable, untiring opponent with the whole world watching, and recounts the history of machine intelligence through the microcosm of chess, considered by generations of scientific pioneers to be a key to unlocking the secrets of human and machine cognition. Kasparov uses his unrivaled experience to look into the future of intelligent machines and sees it bright with possibility. As many critics decry artificial intelligence as a menace, particularly to human jobs, Kasparov shows how humanity can rise to new heights with the help of our most extraordinary creations, rather than fear them. Deep Thinking is a tightly argued case for technological progress, from the man who stood at its precipice with his own career at stake.

    With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. You’ll explore the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples Dive into Spark’s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Spark’s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation

    Or you have persistent pain you and your doctor can't explain. Man or woman, you may be fighting fluctuating hormone levels. Or maybe you snore like a freight train.Anything that narrows the throat and interrupts sleep, particularly breathing problems brought on by sleep position, illness, life changes, or your anatomy, may be key to understanding a host of common health issues. In this groundbreaking book, Dr. Steven Park outlines a simple, rational explanation for what s making you sick, and provides guidance for treatment options that address specific health problems.

    The book covers all of the new CompTIA Security+ 2008 exam objectives and maps to the new Security+ 2008 exam. This updated edition features many all-new topics, including topics new to the CompTIA exams like cross site scripting, SQL injection, rootkits, and virtualization, as well as topics of increasing importance in the industry as a whole, like the latest breeds of attackers, Wi-Fi Protected Access 2, and Microsoft Windows Vista security.

    Here’s a quick guide and easily digestible list of his lies, moronic comments and stupid moves – both past and present – proving he’s by far the least qualified leader in our nation’s history. “101 Facts” was assembled by a group of independent journalists with nearly a century of combined experience. This isn’t an opinion piece. It’s a catalog of actual statements made by Trump in his own words that leave no doubt as to exactly who this person is and why he doesn’t belong in Washington, in business or in civilized society. Part of the proceeds from this book support anti-Trump groups nationwide. Readers who can’t afford the modest price can still read the book entirely free by visiting DCIdiots.com, a new website created to catalog the ongoing misdoings of Trump and other Washington idiots who are being supported by your tax dollars. When your friends ask why you hate Trump, now you’ll have an instant catalog of reasons, along with a website tracking the ongoing insult to America that is the Trump administration. Check out the book, sign up for the online free newsletter, and keep track of the enemies of wisdom with short, easily digestible and sometimes humorous stories delivered weekly to your inbox. Martin Luther King once said, “In the End, we will remember not the words of our enemies, but the silence of our friends.” Don’t be silent. Buy the book, stay informed and support those supporting you.

    Baby becomes distressed at feeding times and refuses to feed or eats very little despite obvious hunger. Why won’t he/she eat? This is a question parents ask numerous health professionals while searching for a solution. Babies are typically diagnosed with one, two or three medical conditions to explain their aversive feeding behavior during brief appointments. Consequently, many parents don’t receive an effective solution from the health professionals they consult. This is why this book is so necessary. Rowena Bennett is an Australian nurse who holds professional qualifications in various nursing fields including pediatrics, midwifery, child health, mental health and lactation consultant. She has over 20 years experience advising parents how to resolve infant feeding and sleeping problems. Rowena has helped over 1000 babies get over their aversion to bottle-feeding and enjoy feeding once again. Parents claim the relief is life changing. In Your Baby’s Bottle-feeding Aversion, Rowena describes the various reasons babies display aversive feeding behavior, explains how the reader can identify the cause, and describes effective solutions. Included are step-by-step instructions on how to resolve a behavioral feeding aversion that occurs as a result of being repeatedly pressured to feed - the most common of all reasons for babies to become averse to feeding. Your Baby’s Bottle-feeding Aversion provides practical professional feeding advice that not only makes good sense, it works!

    Now, I survive off the grid and close to nature, the way we were intended to live: free.s Throughout my 20s, my 30s and 40s, I worked various construction jobs, lived in the Caribbean aboard a sailboat, owned a restaurant, got married and divorced, and raised two kids. There were highs and lows, but one constant: I spent a lot of time working, working, and working some more – and still stressing about money. Finally, in 2013, I spent $12,500 to buy a sturdy 39-foot Ericson sailboat that needed a little work. Since then, I’ve been living full-time aboard the Gypsea Soul, on the water. I outfitted her with rainwater catchment tanks, plus solar panels to power my freezer and navigation instruments. I am usually on the move or keep my boat anchored out in the water, so that I don't have to pay marinas any rent. This let me clear up my debts, and in turn, freed my spirit. Living on a boat, I've met a wild cast of characters and had a ton of adventures -- hilarious ones, but scary ones, too. In the following pages, I'll share those adventures with you, as well as some how-to information for anyone curious about following a similar path. In between chapters, I've interspersed some of my insights, just as I wrote them, taken straight from my Captain's Log. (Don't call it a “diary”! LOL.) I hope that as you read this book, you will feel sailingas though you’re along with me, fruity island drink by your side, the salt and wind in your hair, lost in the amazement of the sea. Most of all, I hope you'll be inspired to go after whatever's been pulling on your heart.

    In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect.Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor.In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile.The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values.This deeply researched and passionate book could not be more timely.Naomi Klein: "This book is downright scary."Ethan Zuckerman, MIT: "Should be required reading."Dorothy Roberts, author of Killing the Black Body: "A must-read for everyone concerned about modern tools of inequality in America."Astra Taylor, author of The People's Platform: "This is the single most important book about technology you will read this year."

    Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data