[PDF.25id] Probability for Statistics and Machine Learning: Fundamentals and Advanced Topics (Springer Texts in Statistics)

Probability for Statistics and Machine Learning: Fundamentals and Advanced Topics (Springer Texts in Statistics)

[PDF.za77] Probability for Statistics and Machine Learning: Fundamentals and Advanced Topics (Springer Texts in Statistics)

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 | #2025463 in Books |  2011-05-27 | Original language:English | PDF # 1 |  9.40 x2.10 x6.40l,2.85 | File type: PDF | 784 pages

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||7 of 8 people found the following review helpful.| Perfect companion for users of probability theory|By Hyokun Yun|I strongly recommend this book as a reference book for those who apply probability theory in their work: computer scientists, applied statisticians, industrial engineers and so on. This book is very comprehensive: in every topic this book discusses, from very basic undergrad facts to modern probability theory resul| ||From the reviews:|“It is a companion second volume to the author’s undergraduate text Fundamentals of Probability: A First course … . The author seeks to provide readers with a comprehensive coverage of probability for students, instructors

This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine learning. It is written in an extremely accessible style, with elaborate motivating discussions and numerous worked out examples and exercises. The book has 20 chapters on a wide range of topics, 423 worked out examples, and 808 exercises. It is unique in its unification of ...

You can specify the type of files you want, for your device.Probability for Statistics and Machine Learning: Fundamentals and Advanced Topics (Springer Texts in Statistics)   |  Anirban DasGupta. Which are the reasons I like to read books. Great story by a great author.

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