Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    A human body draped over the limbs of a cactus. Sand scouring the naked flesh every time the wind blows.A shocking death launches Special Agent Victor Loshak on a new investigation with an ominous message: They know everything. He heads to Tucson, Arizona, where a recent murder spree seems to be linked to the human trafficking conspiracy he's been working in secret for months.Loshak still has dreams about the Kansas City case. Nightmares about the team of techs peeling up the floorboards in a suburban home. Finding the rotting bodies face down in the muddy earth of the crawlspace. A grisly discovery that ultimately led to more questions than answers.Now he may be closer than ever to solving the puzzle.If you follow the conspiracy rabbit hole all the way down, you eventually reach the bottom.The task force working the desert murders seems oblivious to the conspiracy link, and Loshak must tread lightly. He doesn't know who to trust, what information to share.The tendrils of the human trafficking ring lead in all directions outward from that Kansas City crawlspace. Their influence reaches the highest levels of government and law enforcement. They have eyes and ears everywhere.Even with the complications, the Tucson case slowly unravels the web of connections behind the crimes, both the murders and the conspiracy.Questions get answered. Names and faces are laid bare. Puzzle pieces snapping into place at long last.But the revelations bring about the gravest danger yet.

     -Byte, September 1995 I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me! I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up. -Charles Long If you think you're a really good programmer... read [Knuth's] Art of Computer Programming... You should definitely send me a resume if you can read the whole thing. -Bill Gates It's always a pleasure when a problem is hard enough that you have to get the Knuths off the shelf. I find that merely opening one has a very useful terrorizing effect on computers. -Jonathan Laventhol This first volume in the series begins with basic programming concepts and techniques, then focuses more particularly on information structures-the representation of information inside a computer, the structural relationships between data elements and how to deal with them efficiently. Elementary applications are given to simulation, numerical methods, symbolic computing, software and system design. Dozens of simple and important algorithms and techniques have been added to those of the previous edition. The section on mathematical preliminaries has been extensively revised to match present trends in research. Ebook (PDF version) produced by Mathematical Sciences Publishers (MSP), http: //msp.org

    Haskell emerged in the last decade as a standard for lazy functional programming, a programming style where arguments are evaluated only when the value is actually needed. Haskell is a marvellous demonstration tool for logic and maths because its functional character allows implementations to remain very close to the concepts that get implemented, while the laziness permits smooth handling of infinite data structures.This book does not assume the reader to have previous experience with either programming or construction of formal proofs, but acquaintance with mathematical notation, at the level of secondary school mathematics is presumed. Everything one needs to know about mathematical reasoning or programming is explained as we go along. After proper digestion of the material in this book the reader will be able to write interesting programs, reason about their correctness, and document them in a clear fashion. The reader will also have learned how to set up mathematical proofs in a structured way, and how to read and digest mathematical proofs written by others.

    Short-Cut Math is a concise, remarkably clear compendium of about 150 math short-cuts — timesaving tricks that provide faster, easier ways to add, subtract, multiply, and divide.By using the simple foolproof methods in this volume, you can double or triple your calculation speed — even if you always hated math in school. Here's a sampling of the amazingly effective techniques you will learn in minutes: Adding by 10 Groups; No-Carry Addition; Subtraction Without Borrowing; Multiplying by Aliquot Parts; Test for Divisibility by Odd and Even Numbers; Simplifying Dividends and Divisors; Fastest Way to Add or Subtract Any Pair of Fractions; Multiplying and Dividing with Mixed Numbers, and more.The short-cuts in this book require no special math ability. If you can do ordinary arithmetic, you will have no trouble with these methods. There are no complicated formulas or unfamiliar jargon — no long drills or exercises. For each problem, the author provides an explanation of the method and a step-by-step solution. Then the short-cut is applied, with a proof and an explanation of why it works.Students, teachers, businesspeople, accountants, bank tellers, check-out clerks — anyone who uses numbers and wishes to increase his or her speed and arithmetical agility, can benefit from the clear, easy-to-follow techniques given here.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    It splits the mechanical properties chapter into two separate chapters in order to provide additional and expanded coverage of such topics as fatigue, crack propagation and stress, rupture time, and temperature relationships in creep, to name just a few. In addition, all new topics are accompanied by new problems for a stronger understanding of recent developments in the field.

    No matter your interests (sports, movies, politics), your industry (finance, marketing, technology, manufacturing), or the type of organization you work for (big company, nonprofit, small start-up)—your world is awash with data.As a successful manager today, you must be able to make sense of all this information. You need to be conversant with analytical terminology and methods and able to work with quantitative information. This book promises to become your �quantitative literacy" guide—helping you develop the analytical skills you need right now in order to summarize data, find the meaning in it, and extract its value.In Keeping Up with the Quants, authors, professors, and analytics experts Thomas Davenport and Jinho Kim offer practical tools to improve your understanding of data analytics and enhance your thinking and decision making. You’ll gain crucial skills, including:� How to formulate a hypothesis� How to gather and analyze relevant data� How to interpret and communicate analytical results� How to develop habits of quantitative thinking� How to deal effectively with the �quants” in your organizationBig data and the analytics based on it promise to change virtually every industry and business function over the next decade. If you don’t have a business degree or if you aren’t comfortable with statistics and quantitative methods, this book is for you. Keeping Up with the Quants will give you the skills you need to master this new challenge—and gain a significant competitive edge.

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

    Social media is no longer a curiosity on the horizon but a significant part of your marketing mix.While other books explain why social media is critical and how to go about participating, Social Media Metrics focuses on measuring the success of your social media marketing efforts. Success metrics in business are based on business goals where fame does not always equate to fortune. Read this book to determine:Why striving for more Twitter followers or Facebook friends than the competition is a failing strategy How to leverage the time and effort you invest in social media How to convince those who are afraid of new things that social media is a valuable business tool and not just a toy for the overly-wired Knowing what works and what doesn't is terrific, but only in a constant and unchanging world. Social Media Metrics is loaded with specific examples of specific metrics you can use to guide your social media marketing efforts as new means of communication.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    It provides a transition from elementary calculus to advanced courses in real and complex function theory and introduces the reader to some of the abstract thinking that pervades modern analysis.

    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

    County Sheriff’s detective Danny R. Smith put his life on the line for twenty-one years. His career covered some of L.A.’s darkest hours: a crack cocaine epidemic, unprecedented gang warfare, a spike in homicides that stunned the nation, flames lighting the skies while gunfire rang through the nights during the Rodney King riots. There were deadly encounters: fights, pursuits, shootings, and a beating that left him unconscious. A confrontation with a murderous gangster in a dark alley, where only the miraculous malfunction of a fully automatic weapon saved his life. Hardened by the years spent on the streets and the hundreds of deaths and untold numbers of tragedies he would witness, Smith’s frustrations with a dysfunctional system weighed heavily, and his continued pledge to see justice for the victims came at an astronomical personal cost.In this no-holds-barred memoir, Smith reveals the shocking imagery of fallen colleagues, murdered children, gang warfare, and a Native American who was tortured and burned alive by skinheads. And through his unique insights battling PTSD and being forced to leave the profession he loved, his story will offer new insight into the aftermath of working in law enforcement.Nothing Left to Prove is by turns shocking, terrifying, poignant, and thought-provoking. It’s the very personal story of one man’s career and its effect on his life afterwards, unveiled through Smith’s masterful storytelling. If you think you know cops, if you love compelling true-crime stories, then you’ll love Danny R. Smith’s powerful narrative.

    This is because a child is absolutely captivated by animals. The encyclopedia of animals is especially appealing to all kids. Kids are fascinated by any book on animals. Animal books are loved by kids and the animals do indeed inspire them. Kids will be completely entertained and will stay interested with a book that holds their interest. Kids love learning about the animals.