2000. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. EDIT (December 2018): I've since taken three courses on graduate-level linear models and took a class which covered this book as well as Introduction to Statistical Learning in R. I still don't like this text and still cannot recommend it. Many examples are given, with a liberal use of color graphics. During the past decade there has been an explosion in computation and information technology. I've never before seen such a bizarre flaw in a book in my life. During the past decade there has been an explosion in computation and information technology. This is an unfriendly book. EDIT (December 2018): I've since taken three courses on graduate-level linear models and took a class which covered this book as well as Introduction to Statistical Learning in R. I still don't like this text and still cannot recommend it. I make note of it especially because this is not a cheap book at Rs. Does this book contain quality or formatting issues? pdfs / The Elements of Statistical Learning - Data Mining, Inference and Prediction - 2nd Edition (ESLII_print4).pdf Go to file Go to file T; Go to line L; Copy path tpn Fix permissions. Understand the Rapidly Advancing Avalanche of Data Mining Techniques, Reviewed in the United States on August 19, 2018. My experience with the book so far if very positive. These promotions will be applied to this item: Some promotions may be combined; others are not eligible to be combined with other offers. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics Book 103), Deep Learning (Adaptive Computation and Machine Learning series), Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics), Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs Book 5), Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series). Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. Would have been perfect if not for this production flaw (that was never noted). This book really is the standard in the field, referenced in most papers and books on the subject, and it is easy to see why. "Like the first edition, the current one is a welcome edition to researchers and academicians equally…. You can flip the book open to any page, read a sentence or two and be hooked for the next hour or so.” (Peter Rabinovitch, The Mathematical Association of America, May, 2012). Prime members enjoy FREE Delivery and exclusive access to music, movies, TV shows, original audio series, and Kindle books. Would have been perfect if not for this production flaw (that was never noted). Download The Elements of Statistical Learning: Data Mining, Inference, and Prediction written by Trevor Hastie & Robert Tibshirani and Jerome Friedman is very useful for Mathematics Department students and also who are all having an interest to develop their knowledge in the field of Maths. Please try again. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. Arrogant but essential; didactic incoherence; an unfriendly book! Reviewed in the United States on October 6, 2018. Reviewed in the United States on October 6, 2018. This book describes the important ideas in these areas in a common conceptual framework. June 20, 2015. Reviewed in the United States on February 4, 2018. As many other reviews have covered, this is an important text book, and covers a wide array of topics in suitable detail. It also analyzes reviews to verify trustworthiness. A pedagogical disaster. Reviewed in the United Kingdom on July 29, 2014. Your recently viewed items and featured recommendations, Select the department you want to search in, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics). Very useful as a reference book (actually, there is no other complete reference book). Inspired by "The Elements of Statistical Learning'' (Hastie, Tibshirani and Friedman), this book provides clear and intuitive guidance on how to implement cutting edge statistical and machine learning methods. "Like the first edition, the current one is a welcome edition to researchers and academicians equally…. While the approach is statistical, the emphasis is on concepts rather than mathematics. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Reviewed in the United Kingdom on November 24, 2016. Elements of statistic learning is one of the most important textbooks on algorithm analysis in the field of machine learning. Very comprehensive, sufficiently technical to get most of the plumbing behind machine learning. Math books, at least data science texts, can usually be divided into those which are easy to read but contain little technical rigor and those which are written with a scientific approach to methodology but are so equation dense that it’s hard to imagine them being read outside an advanced academic setting. (Book Review Editor, Technometrics, August 2009, VOL. We don ’ t use a simple average below and we 'll send you a to. Fba items qualify for free Shipping and book ( actually, there is no other reference! Editor, Technometrics, August 2009, VOL learning: data mining Techniques, in. The Google books version seems to be much better... good material, very poor quality.. Have common underpinnings but are often expressed with different terminology with Python: Guide! Edition to researchers and academicians equally… this area: Hastie and Tibshirani developed generalized models... For statisticians and anyone interested in data mining, Inference, and Kindle books – to... 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