This straight-talking, empowering video program offers essential information on how problem gambling develops, its damaging impact on individuals and families, and how it can successfully be treated. Through candid first-hand accounts from four recovering gamblers, along with illuminating commentary from mental health experts, the program shows gamblers, their families, and therapists: *How an alluring diversion becomes a shameful secret as problem gambling takes hold *Common myths and misperceptions about gambling--and why winning big is so unlikely *The benefits of individual and group therapy and self-help approaches *Ways to overcome setbacks in recovery and make meaningful, lasting changes Winner--CINE Golden Eagle Award

Michael Walker's Laurel Canyon presents the inside story of the once hottest rock and roll neighborhood in LA. In the late sixties and early seventies, an impromptu collection of musicians colonized a eucalyptus-scented canyon deep in the Hollywood Hills of Los Angeles and melded folk, rock, and savvy American pop into a sound that conquered the world as thoroughly as the songs of the Beatles and the Rolling Stones had before them. Thirty years later, the music made in Laurel Canyon continues to pour from radios, iPods, and concert stages around the world. During the canyon's golden era, the musicians who lived and worked there scored dozens of landmark hits, from California Dreamin' to Suite: Judy Blue Eyes to It's Too Late, selling tens of millions of records and resetting the thermostat of pop culture. In Laurel Canyon, veteran journalist Michael Walker tells the inside story of this unprecedented gathering of some of the baby boomer's leading musical lights--including Joni Mitchell; Jim Morrison; Crosby, Stills, and Nash; John Mayall; the Mamas and the Papas; Carole King; the Eagles; and Frank Zappa, to name just a few--who turned Los Angeles into the music capital of the world and forever changed the way popular music is recorded, marketed, and consumed.

This third edition of Reconstructing Quaternary Environments has been completely revised and updated to provide a new account of the history and scale of environmental changes during the Quaternary. The evidence is extremely diverse ranging from landforms and sediments to fossil assemblages and geochemical data, and includes new data from terrestrial, marine and ice-core records. Dating methods are described and evaluated, while the principles and practices of Quaternary stratigraphy are also discussed. The volume concludes with a new chapter which considers some of the key questions about the nature, causes and consequences of global climatic and environmental change over a range of temporal scales. This synthesis builds on the methods and approaches described earlier in the book to show how a number of exciting ideas that have emerged over the last two decades are providing new insights into the operation of the global earth-ocean-atmosphere system, and are now central to many areas of contemporary Quaternary research. This comprehensive and dynamic textbook is richly illustrated throughout with full-colour figures and photographs. The book will be of interest to undergraduates, postgraduates and professionals in Earth Science, Environmental Science, Physical Geography, Geology, Botany, Zoology, Ecology, Archaeology and Anthropology

The popular and critical successes of films like The Sixth Sense and The Ring and its sequels in the late 1990s led to an impressive international explosion of scary films dealing with ghosts. This book takes a close look at a number of those films from different countries, including the United States, Japan, South Korea, Spain, and Great Britain. Making a crucial distinction between these atmospheric films and conventional horror, Michael Walker argues that they are most productively seen as ghost melodramas, which opens them up to a powerful range of analytic tools from the study of melodrama, including, crucially, psychoanalysis.

The food supply chain needs to reassure consumers and businesses about the safety and standards of food. Global estimates of the cost of food fraud to economies run into billions of dollars hence a huge surge in interest in food authenticity and means of detecting and preventing food fraud and food crime. Approaches targeting DNA markers have assumed a pre-eminence. This book is the most comprehensive and timely collection of material from those working at the forefront of DNA techniques applied to food authenticity. Addressing the new field of analytical molecular biology as it combines the quality assurance rigour of analytical chemistry with DNA techniques, it introduces the science behind DNA as a target analyte, its extraction, amplification, detection and quantitation as applied to the detection of food fraud and food crime. Making the link with traditional forensic DNA profiling and describing emerging and cutting-edge techniques such as next generation sequencing, this book presents real-world case studies from a wide perspective including from analytical service providers, industry, enforcement agencies and academics. It will appeal to food testing laboratories worldwide, who are just starting to use these techniques and students of molecular biology, food science and food integrity. Food policy professionals and regulatory organisations who will be using these techniques to back up legislation and regulation will find the text invaluable. Those in the food industry in regulatory and technical roles will want to have this book on their desks.

Explore supercharged machine learning techniques to take care of your data laundry loads Key Features Learn how to prepare data for machine learning processes Understand which algorithms are based on prediction objectives and the properties of the data Explore how to interpret and evaluate the results from machine learning Book DescriptionMany individuals who know how to run machine learning algorithms do not have a good sense of the statistical assumptions they make and how to match the properties of the data to the algorithm for the best results. As you start with this book, models are carefully chosen to help you grasp the underlying data, including in-feature importance and correlation, and the distribution of features and targets. The first two parts of the book introduce you to techniques for preparing data for ML algorithms, without being bashful about using some ML techniques for data cleaning, including anomaly detection and feature selection. The book then helps you apply that knowledge to a wide variety of ML tasks. You'll gain an understanding of popular supervised and unsupervised algorithms, how to prepare data for them, and how to evaluate them. Next, you'll build models and understand the relationships in your data, as well as perform cleaning and exploration tasks with that data. You'll make quick progress in studying the distribution of variables, identifying anomalies, and examining bivariate relationships, as you focus more on the accuracy of predictions in this book. By the end of this book, you'll be able to deal with complex data problems using unsupervised ML algorithms like principal component analysis and k-means clustering. What you will learn Explore essential data cleaning and exploration techniques to be used before running the most popular machine learning algorithms Understand how to perform preprocessing and feature selection, and how to set up the data for testing and validation Model continuous targets with supervised learning algorithms Model binary and multiclass targets with supervised learning algorithms Execute clustering and dimension reduction with unsupervised learning algorithms Understand how to use regression trees to model a continuous target Who this book is forThis book is for professional data scientists, particularly those in the first few years of their career, or more experienced analysts who are relatively new to machine learning. Readers should have prior knowledge of concepts in statistics typically taught in an undergraduate introductory course as well as beginner-level experience in manipulating data programmatically.