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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.
The author, a computer science professor diagnosed with terminal cancer, explores his life, the lessons that he has learned, how he has worked to achieve his childhood dreams, and the effect of his diagnosis on him and his family.
Jim Sain's star is rising! Life in Berkeley is as colorful as ever, and now, his life is even more bizarre than before just like he likes it. Despite his madness, buff oonery, and lefty leanings, Berkeley's zany mayor continues to be a media darling. Back for more, Jack McLaughlin's love song for Berkeley continues in mR. bERZERKELEY II. Jim's trying his best to navigate the waters, but Big Game antics and even bigger lies spun by his enemies are making it a rough crossing. And now that he's a father, he's out to lead the willing and find solutions for all the many challenges he now faces including a few surprises. His life is filled with real characters, as the expression goes: Nymphomaniac Jasmine is leading Josh toward the altar, while the pregnant Babe has escaped to Kansas, leaving Winnie to handle Hamilton House alone. Freshman Sarah changes lifestyles again and lesbian lovers Stephanie and Judy want to experience motherhood. Mysterious Michael and his mother, the evil vice chancellor, continue their hatred toward each other. Asia's bordello past and a murder put her future (and the chancellor's reputation) in danger. Former boarder Ainsley Bassette reappears on the scene; Bessie faces a life-or-death operation; and now, Trojan's fighting a deadly battle with coyotes. Toss in a little naked windsurfing on Southern California beaches and a trip to Disneyland, and you've got another exciting installment of wacky mR. bERZERKELEY adventures.
A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
Stanford Wong is in big trouble--or as he would spell it, "trubble"--in this laugh-out-loud companion to the award-winning Millicent Min, Girl Genius. Stanford Wong is having a bad summer. If he flunks his summer-school English class, he won't pass sixth grade. If that happens, he won't start on the A-team. If that happens, his friends will abandon him and Emily Ebers won't like him anymore. And if THAT happens, his life will be over. Then his parents are fighting, his grandmother Yin-Yin hates her new nursing home, he's being "tutored" by the world's biggest nerdball, Millicent Min--and he's not sure his ballpoint "Emily" tattoo is ever going to wash off.But Stanford Wong has a few things going for him. He has Yin-Yin's fantastic dim sum. He has his magic jade pendant, source of all his basketball skill. He has this amazing new book called The Outsiders he's just discovered. He may even have Millicent. And Stanford realizes that that might just be enough to save his summer--if he can pull it all together in time.
Ruth E. Sheets, author of From Darkness to Light, presents God's Love. This novel portrays the pain and tragedy that occurs to military persons and their families due to war. Ruth is a registered nurse and has worked with the physically and mentally afflicted. She is a minister and has assisted in prison ministry.