Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.

    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

    Meet Bina48, the world's most sentient robot, commissioned by Martine Rothblatt and created by Hanson Robotics. Bina48 is a nascent Mindclone of Martine's wife that can engage in conversation, answer questions, and even have spontaneous thoughts that are derived from multimedia data in a Mindfile created by the real Bina. If you're active on Twitter or Facebook, share photos through Instagram, or blogging regularly, you're already on your way to creating a Mindfile—a digital database of your thoughts, memories, feelings, and opinions that is essentially a back-up copy of your mind. Soon, this Mindfile can be made conscious with special software—Mindware—that mimics the way human brains organize information, create emotions and achieve self-awareness. This may sound like science-fiction A.I. (artificial intelligence), but the nascent technology already exists. Thousands of software engineers across the globe are working to create cyberconsciousness based on human consciousness and the Obama administration recently announced plans to invest in a decade-long Brain Activity Map project. Virtually Human is the only book to examine the ethical issues relating to cyberconsciousness and Rothblatt, with a Ph.D. in medical ethics, is uniquely qualified to lead the dialogue.

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    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.

    In On Being Certain, neurologist Robert Burton challenges the notions of how we think about what we know. He shows that the feeling of certainty we have when we know something comes from sources beyond our control and knowledge. In fact, certainty is a mental sensation, rather than evidence of fact. Because this feeling of knowing seems like confirmation of knowledge, we tend to think of it as a product of reason. But an increasing body of evidence suggests that feelings such as certainty stem from primitive areas of the brain, and are independent of active, conscious reflection and reasoning. The feeling of knowing happens to us; we cannot make it happen. Bringing together cutting edge neuroscience, experimental data, and fascinating anecdotes, Robert Burton explores the inconsistent and sometimes paradoxical relationship between our thoughts and what we actually know. Provocative and groundbreaking, On Being Certain, will challenge what you know (or think you know) about the mind, knowledge, and reason.

    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.

    It’s time we stand face-to-digital-face with the true powers and limitations of the algorithms that already automate important decisions in healthcare, transportation, crime, and commerce. Hello World is indispensable preparation for the moral quandaries of a world run by code, and with the unfailingly entertaining Hannah Fry as our guide, we’ll be discussing these issues long after the last page is turned.

    What is going on? Anatomy of an Epidemic challenges readers to think through that question themselves. First, Whitaker investigates what is known today about the biological causes of mental disorders. Do psychiatric medications fix “chemical imbalances” in the brain, or do they, in fact, create them? Researchers spent decades studying that question, and by the late 1980s, they had their answer. Readers will be startled—and dismayed—to discover what was reported in the scientific journals. Then comes the scientific query at the heart of this book: During the past fifty years, when investigators looked at how psychiatric drugs affected long-term outcomes, what did they find? Did they discover that the drugs help people stay well? Function better? Enjoy good physical health? Or did they find that these medications, for some paradoxical reason, increase the likelihood that people will become chronically ill, less able to function well, more prone to physical illness?  This is the first book to look at the merits of psychiatric medications through the prism of long-term results. Are long-term recovery rates higher for medicated or unmedicated schizophrenia patients? Does taking an antidepressant decrease or increase the risk that a depressed person will become disabled by the disorder? Do bipolar patients fare better today than they did forty years ago, or much worse? When the National Institute of Mental Health (NIMH) studied the long-term outcomes of children with ADHD, did they determine that stimulants provide any benefit?  By the end of this review of the outcomes literature, readers are certain to have a haunting question of their own: Why have the results from these long-term studies—all of which point to the same startling conclusion—been kept from the public?  In this compelling history, Whitaker also tells the personal stories of children and adults swept up in this epidemic. Finally, he reports on innovative programs of psychiatric care in Europe and the United States that are producing good long-term outcomes. Our nation has been hit by an epidemic of disabling mental illness, and yet, as Anatomy of an Epidemic reveals, the medical blueprints for curbing that epidemic have already been drawn up.

    Mind Children, written by an internationally renowned roboticist, offers a comparable experience--a mind-boggling glimpse of a world we may soon share with our artificial progeny. Filled with fresh ideas and insights, this book is one of the most engaging and controversial visions of the future ever written by a serious scholar.Hans Moravec convincingly argues that we are approaching a watershed in the history of life--a time when the boundaries between biological and postbiological intelligence will begin to dissolve. Within forty years, Moravec believes, we will achieve human equivalence in our machines, not only in their capacity to reason but also in their ability to perceive, interact with, and change their complex environment. The critical factor is mobility. A computer rooted to one place is doomed to static iterations, whereas a machine on the prowl, like a mobile organism, must evolve a richer fund of knowledge about an ever-changing world upon which to base its actions.In order to achieve anything near human equivalence, robots will need, at the least, the capacity to perform ten trillion calculations per second. Given the trillion-fold increase in computational power since the end of the nineteenth century, and the promise of exotic technologies far surpassing the now-familiar lasers and even superconductors, Moravec concludes that our hardware will have no trouble meeting this forty-year timetable.But human equivalence is just the beginning, not an upper bound. Once the tireless thinking capacity of robots is directed to the problem of their own improvement and reproduction, even the sky will not limit their voracious exploration of the universe. In the concluding chapters Moravec challenges us to imagine with him the possibilities and pitfalls of such a scenario. Rather than warning us of takeover by robots, the author invites us, as we approach the end of this millennium, to speculate about a plausible, wonderful postbiological future and the ways in which our minds might participate in its unfolding.

    Every new reader's brain possesses the extraordinary capacity to rearrange itself beyond its original abilities in order to understand written symbols. But how does the brain learn to read? As world-renowned cognitive neuroscientist and scholar of reading Maryanne Wolf explains in this impassioned book, we taught our brain to read only a few thousand years ago, and in the process changed the intellectual evolution of our species.Wolf tells us that the brain that examined tiny clay tablets in the cuneiform script of the Sumerians is configured differently from the brain that reads alphabets or of one literate in today's technology.There are critical implications to such an evolving brain. Just as writing reduced the need for memory, the proliferation of information and the particular requirements of digital culture may short-circuit some of written language's unique contributions—with potentially profound consequences for our future.Turning her attention to the development of the individual reading brain, Wolf draws on her expertise in dyslexia to investigate what happens when the brain finds it difficult to read. Interweaving her vast knowledge of neuroscience, psychology, literature, and linguistics, Wolf takes the reader from the brains of a pre-literate Homer to a literacy-ambivalent Plato, from an infant listening to Goodnight Moon to an expert reader of Proust, and finally to an often misunderstood child with dyslexia whose gifts may be as real as the challenges he or she faces.As we come to appreciate how the evolution and development of reading have changed the very arrangement of our brain and our intellectual life, we begin to realize with ever greater comprehension that we truly are what we read. Ambitious, provocative, and rich with examples, Proust and the Squid celebrates reading, one of the single most remarkable inventions in history. Once embarked on this magnificent story of the reading brain, you will never again take for granted your ability to absorb the written word.

    Introducing students to the many facets of neural networks, this text provides many case studies to illustrate their real-life, practical applications.

    He traces AI's origins in ancient myth, through literary classics like Frankenstein, to today's sci-fi blockbusters, arguing that a fascination with AI is hardwired into the human psyche. He explains AI's history, technology, and potential; its manifestations in intelligent machines; its connections to neurology and consciousness, as well as—perhaps most tellingly—what AI reveals about us as human beings.In Our Own Image argues that we are on the brink of a fourth industrial revolution—poised to enter the age of Artificial Intelligence as science fiction becomes science fact. Ultimately, Zarkadakis observes, the fate of AI has profound implications for the future of science and humanity itself.

    The New Mind Readers provides a compelling look at the origins, development, and future of these extraordinary tools, revealing how they are increasingly being used to decode our thoughts and experiences--and how this raises sometimes troubling questions about their application in domains such as marketing, politics, and the law.Russell Poldrack takes readers on a journey of scientific discovery, telling the stories of the visionaries behind these breakthroughs. Along the way, he gives an insider's perspective on what is perhaps the single most important technology in cognitive neuroscience today--functional magnetic resonance imaging, or fMRI, which is providing astonishing new insights into the contents and workings of the mind. He highlights both the amazing power and major limitations of these techniques and describes how applications outside the lab often exceed the bounds of responsible science. Poldrack also details the unique and sometimes disorienting experience of having his own brain scanned more than a hundred times as part of a landmark study of how human brain function changes over time.Written by one of the world's leading pioneers in the field, The New Mind Readers cuts through the hype and misperceptions surrounding these emerging new methods, offering needed perspective on what they can and cannot do--and demonstrating how they can provide new answers to age-old questions about the nature of consciousness and what it means to be human.

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.