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.

    

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    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

    Women and Sabarimala is a rare book and is written from a woman’s perspective, explaining the nature of the temple through India’s traditional knowledge systems, such as Ayurveda, Chakras, Tantra and Agama Shastra. At the same time, the author’s personal experiences simplify the understanding of these deep sciences, providing a glimpse into how temples impact the human physiology and, in particular, women’s menstrual cycles. This book will change the way Hindu temples, especially Sabarimala, are perceived and experienced.

    Although it has a long history, the recent discovery (1992) of the body's widespread endocannabinoid system (ECS) has thrust cannabis back into the limelight again as a viable medicine. In 2012 over 2.5 million prescriptions were written for medical marijuana in the United States. CBD and THC are both cannabinoids found in cannabis. However, while THC produces a “high” in the user, CBD does not. And now legal CBD-rich hemp oil is available over-the-counter in all 50 states, without a prescription. It was discovered that the Hemp Family of plants (cannabis, marijuana) is loaded with cannabinoids that stimulate our ECS receptor sites. These sites are found in the brain, organs, glands, connective tissue and immune cells and plays regulatory roles in many physiological processes including appetite, pain-sensation, mood and memory. The primary purpose of this system revolves around maintaining balance in the body. Cannabinoids found in all varieties of cannabis work in harmony with the cannabinoids we naturally produce when our system is functioning properly. It is now coming to light that we may very well be “Endocannabinoid Deficient” and supplementing with Cannabidiol, known as CBD, may provide just what we’re missing to restore optimum health. The health benefits of cannabidiol (CBD) from natural hemp oil is this book's primary focus. It explores the similarities, differences, uses and benefits of hemp, cannabis and medical marijuana along with the interplay of THC and CBD. Their 480 other components are also discussed, such as terpenoids, flavonoids, enzymes, vitamins, etc. Make no mistake about it, the endocannabinoid system, although newly discovered, is just as important as any other bodily system, like the muscular, cardiac, circulatory or digestive system. The ECS requires its own specialized medicine as found in the Hemp Family of plants, which is also known as cannabis, and which includes all strains of marijuana. Here is a list of conditions known and/or being researched that may be helped by cannabinoid therapeutics and supplementation: Acne ADD/ADHD Addiction AIDS ALS (Lou Gehrig's Disease) Alzheimer’s Anorexia Antibiotic Resistance Anxiety Atherosclerosis Arthritis Asthma Autism Bipolar Cancer Colitis/Crohn’s Depression Diabetes Endocrine Disorders Epilepsy/Seizure Fibromyalgia Glaucoma Heart Disease Huntington’s Inflammation Irritable Bowel Kidney Disease Liver Disease Metabolic Syndrome Migraine Mood Disorders Motion Sickness Multiple Sclerosis Nausea Neurodegeneration Neuropathic Pain Obesity OCD Osteoporosis Parkinson’s Prion/Mad Cow Disease PTSD Rheumatism Schizophrenia Sickle Cell Anemia Skin Conditions Sleep Disorders Spinal Cord Injury Stress Stroke/TBI 10% of the proceeds from sales of this book will be donated to the American Cannabis Nurses Association in an effort to bring together nurses, to share, integrate and one day certify nurses in the science of endocannabinoid therapeutics in nursing practice.

    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

    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.

    It’s about the re-making of your interior world as the exterior world becomes more unfamiliar and uncertain.The sudden arrival of the pandemic pushed the world faster and further into the 21st century. Now, life is dictated by two forces you can’t see: data and the virus. Are you really built for so much change so quickly?Basar/Coupland/Obrist’s prequel, The Age of Earthquakes: A Guide to the Extreme Present, became an instant cult classic. It’s been described as, “a mediation on the madness of our media,” and, “an abstract representation of how we feel about our digital world.”Like that book, The Extreme Self collapses comedy and calamity at the speed of swipe. Dazzling images are sourced from over 70 of the world’s foremost artists, photographers, technologists and musicians, while Daly & Lyon’s kinetic design elevates the language of memes into a manifesto. Over fourteen timely chapters, The Extreme Self tours through fame and intimacy, post-work and new crowds, identity crisis and eternity. This is an eye-opening, provocative portrait of what’s really happening to YOU.

    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

    On a tight budget, she’s thrilled to discover a charming fixer-upper and jumps to make an offer. But it isn’t until after she’s signed the paperwork that she learns there’s more to the foreclosure than a few loose floorboards… Annette Best owns Best on the Block realty, but the business is struggling. Then a new face comes to town, and Annette sees an opportunity to save her company… as long as no one finds out about the history of Apple Hill Lane.Judith Banks is freshly single but too fed up to date. Or so she thinks. Then a new neighbor moves in on her street, and brings with her a team of pros–electricians and plumbers and all the sorts of men Judith never expected to find attractive. Soon enough, she’s drawn to one particular worker, someone who happens to know about the house’s storied history.Beverly Castle had it all. Now she’s lost it all, and the only thing keeping her going is her job with the Harbor Herald. She needs something else: a good friend. When the arrival of a new neighbor inspires her to investigate, she finds that she isn’t the only one curious about the house on Apple Hill… or the woman who now lives there.If you enjoyed the Birch Harbor series, you will fall in love with Harbor Hills, a Birch Harbor spinoff. Romance, secrets and mystery, family ties and female friendships abound in this heartwarming saga about four women who find friendship right next door.

    Her new life is strange and confusing and sometimes frightening. Amanda can barely understand Arabic and the treatment of the women of the family seems wrong to a girl raised in Wales. To add to her problems, Mohammed proves to be verbally and physically abusive - especially once they have their own flat away from the protection of the wider family. Somehow Amanda must escape, but not without her children.

    One primary theme is the question, How is a speaker's communicative intent recognized? Rather than treat phonology, phonetics, morphology, syntax, semantics, and pragmatics as completely separate fields, the text shows how they interact in principled ways. Similarly, language variation and acquisition are informed by results in these fields. The text provides a sound introduction to linguistic methodology while also revealing why people are intrinsically interested in language -- the ultimate puzzle of the human mind.The fifth edition has been thoroughly revised. Revisions include, but are not limited to, the addition of selected readings sections, updated examples, new discussion on the creative nature of neologisms, and the use of IPA as the primary transcription system throughout. This edition also includes an account of the patterns of occurrence of reduced vowels in English. An understanding of these patterns enables the reader to write a phonemic transcription of any English word.

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

    It reflects the latest information (in 2001), including the impact of global competition and rapid technological advances, that have accelerated trends such as shared service centres, outsourcing and just-in-time training. A number of actual company examples demonstrates how concepts are being used in several leading-edge organizations.