An excellent corrective to the Hollywood version of cops and crime.’ Miles Corwin ‘These are stories told by one cop to another - raw, unfiltered and funny. This book is both laugh-out-loud hilarious and moving.’ Jane Bussman WE ARE THE COPS is an adrenalin-fuelled ride through the lives of America’s police, told in the authentic voices of the cops themselves. The journey begins with the rookie’s first day on the job, and moves through the heartbreak of officers dying in the line of duty, the bloody reality of policing savage gang wars, the devastating consequences of drug crime, a gut-wrenching cop’s eye view of 9/11, and even an encounter with a runaway gorilla called Little Joe. These real-life stories from crime fighting’s front line come from cops of every rank, from chiefs to street cops, working in big cities and small towns all over the US. The result is a stunning montage of brutal, funny and sometimes tragic true events which paints a vivid and unforgettable portrait of life as an American cop.

    From the 1960s graffiti proclaiming 'Clapton is God', to his seminal work in supergroup Cream and his phenomenally successful solo career, Eric Clapton has achieved the status of bona fide living legend and enduring icon.Now in his sixth decade in the music business, he occupies an exulted position at the pinnacle of the rock world thanks to songs like Layla, Wonderful Tonight and Tears In Heaven, and for many is considered the greatest guitarist who ever lived.This book will chart his rise to stardom in the 60s and his unparalleled success since walking out of the Yardbirds as a 20-year-old to follow his chosen path of the blues with John Mayall's Bluesbreakers and later with Jack Bruce and Ginger Baker in supergroup Cream, as well as his successful solo career. However, his success has come at a price. Once a happy well-adjusted boy, the young Clapton was devastated by the realisation at the age of nine that the woman he thought was his sister was in fact his mother, and that the couple he thought were his parents were his maternal grandparents. His treatment by his mother was also to shape his future turbulent relationships with the women in his life, including his failed first marriage to model Pattie Boyd, who was married to Clapton's close friend George Harrison when he fell for her. Motherless Child also chronicles his battles with the demons of drugs and alcohol, his successful journey to sobriety, and examines his legacy as one of the most influential musicans of his generation.This is essential reading for any Clapton fan.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    It's all fun so get inspired and tangle something! Learn to color with chalks, watercolors, pencils and pens; add bling with glitter, jewels, and sparkly inks.

    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.

    Cloud computing is rapidly transitioning from a niche technology embraced by startups and tech-forward companies to the foundation upon which enterprise systems build their future. In order to compete in today’s marketplace, organizations large and small are embracing cloud architectures and practices.

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    Following the death of her parents, Christine goes to live on a housing scheme with her sister Kirsty, her brother-in-law and niece. But while existence on the housing scheme leaves much to be desired, Christine is as determined as ever to live a full and happy life. With much humour, warmth and charm, Fraser explores the realities of growing up in a wheelchair, as well as her experiences of working in a factory, of finding love, and of beginning what would become a successful writing career. Set against the evocative backdrop of the Scottish Highlands, Roses Round the Door is a heart-warming tale that is every bit as delightful and moving as Blue Above the Chimneys. Praise for Christine Marion Fraser ‘Christine Marion Fraser writes characters so real they almost leap out of the pages… you would swear she must have grown up with them.’ — The Sun ‘Christine Marion Fraser weaves an intriguing story in which the characters are alive against a spellbinding background'— Yorkshire Herald Fraser writes with a great depth of feeling and has the knack of making her characters come alive. She paints beautiful pictures of the countryside and their changing seasons — Aberdeen Express Full-blooded romance, a strong, authentic setting — The Scotsman Christine Marion Fraser (1938-2002) was one of Scotland's best-selling authors. She was the author of the much-loved Rhanna series, a Scottish saga set on the Hebridean island of Rhanna. She also wrote the acclaimed King’s Croft series as well as the Noble series. Christine’s formative years were spent in the post-war Govan district of Glasgow and she spent her later life in Argyll with her husband.

    The data world was revolutionized a few years ago when Hadoop and other tools made it possible to getthe results from queries in minutes. But the revolution continues. Analysts now demand sub-second, near real-time query results. Fortunately, we have the tools to deliver them. This report examines tools and technologies that are driving real-time big data analytics.

    There has to be something better.You don't need a new garden; you just need to learn how to dig! In Acres of Diamonds, pastor and New York Times bestselling author Jentezen Franklin helps you discover the unfathomable riches Jesus Christ has for you. Rather than chase after a better life, you can celebrate the untold spiritual provision to be found even in the midst of spiritual deprivation. Readers will learn to cherish where God has placed them as they uncover the hidden potential within their families, jobs, ministries, and communities . . . right where they are.

    You can get a cup at any caf, sandwich bar or restaurant anywhere. So how did Starbucks manage to reinvent coffee as a whole new experience, and create a hugely successful brand in the process? The Starbucks Story tells the brand's story from its origins in a Seattle fish market to its growing global presence today. This is a story that has unfolded quickly - at least in terms of conventional business development. Starbucks is a phenomenon. Unknown 15 years ago, it now ranks among the 100 most valuable brands in the world. It has become the quintessential brand of the modern age, built around the creation of an experience that can be consistently reproduced across the world. Originally published in 2004 as 'My Sister's A Barista: How they made Starbucks a home away from home', this new 2012 edition has been updated to bring the brand up to date.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    Prepare for exams and succeed in your mathematics course with this comprehensive solutions manual! Featuring worked out-solutions to the problems in CALCULUS: THE CLASSIC EDITION, 5th Edition, this manual shows you how to approach and solve problems using the same step-by-step explanations found in your textbook examples.

    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

    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