[PDF.55jl] Understanding Machine Learning: From Theory to Algorithms

Understanding Machine Learning: From Theory to Algorithms

[PDF.ul35] Understanding Machine Learning: From Theory to Algorithms

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 | #218250 in Books |  Shai Shalev Shwartz Shai Ben David |  2014-05-19 | Original language:English | PDF # 1 |  9.96 x1.10 x6.97l,1.95 | File type: PDF | 410 pages

 | Understanding Machine Learning From Theory to Algorithms

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||31 of 33 people found the following review helpful.| Excellent book based on statistical learning theory|By Yung-Hsuan Chao|This book provides a great story line along with solid proofs of machine learning theories and algorithms.
Each chapter is rather short (15-20 pages), yet is well written to convey the topic in detail, making the book comfortable to read.
Moreover, the connection among consecutive chapters is str| |"This elegant book covers both rigorous theory and practical methods of machine learning. This makes it a rather unique resource, ideal for all those who want to understand how to find structure in data." |Bernhard Schölkopf, Max Planck Institute for Inte

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics of the field,...

You easily download any file type for your device.Understanding Machine Learning: From Theory to Algorithms   |  Shai Shalev-Shwartz, Shai Ben-David. A good, fresh read, highly recommended.

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