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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 two-time Grammy Award-winning singer and songwriter bares her
heart and soul in this intimate memoir, a story of music, stardom,
love, family, heritage, and resilience. She inspired songs-Leon
Russell wrote "A Song for You" and "Delta Lady" for her, Stephen
Stills wrote "Cherokee." She co-wrote songs-"Superstar" and the
piano coda to "Layla," uncredited. She sang backup for Eric
Clapton, Joe Cocker, and Stills, before finding fame as a solo
artist with such hits as "We're All Alone" and "(Your Love Has
Lifted Me) Higher and Higher." Following her story from Lafayette,
Tennessee to becoming one of the most sought after rock vocalists
in LA in the 1970s, Delta Lady chronicles Rita Coolidge's
fascinating journey throughout the '60s-'70s pop/rock universe. A
muse to some of the twentieth century's most influential rock
musicians, she broke hearts, and broke up bands. Her relationship
with drummer Jim Gordon took a violent turn during the legendary
1970 Mad Dogs & Englishmen tour; David Crosby maintained that
her triangle with Stills and Graham Nash was the last straw for the
group. Her volatile six-year marriage to Kris Kristofferson yielded
two Grammys, a daughter, and one of the Baby Boom generation's epic
love stories. Throughout it all, her strength, resilience, and
inner and outer beauty-along with her strong sense of heritage and
devotion to her family-helped her to not only survive, but thrive.
Co-written with best-selling author Michael Walker, Delta Lady is a
rich, deeply personal memoir that offers a front row seat to an
iconic era, and illuminates the life of an artist whose career has
helped shape modern American culture.
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.
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.
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