Statistics for Machine Learning

by Pratap Dangeti

Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. You will also design programs for performing tasks such as model, parameter fitting, regression, classification, density collection, and more.

By the end of the book, you will have mastered the required statistics for Machine Learning and will be able to apply your new skills to any sort of industry problem.

Genres: Computer Science, Artificial Intelligence, Programming, Nonfiction

442 pages, Unknown Binding

Published January 1, 2017

Reviews

[An · Rating 3 out of 5]

Maybe it's just my reading style, but I felt I only learned the overview of the topic rather than feeling like I've obtained some deeper understanding. It's still perfectly fine for getting and overview, and again this is perhaps my own deficient learning style, but I would have preferred if it studied a few techniques in much more depth, especially at the algorithmic level.

[Stein Karlsen · Rating 5 out of 5]

Great introduction to many statistical terms and concepts.

[Atanu Shome · Rating 2 out of 5]

It started good. But gradually looses the momentum. Felt like you already need to know many things prior reading it. Less example and description is making it hard to understand.

[Delhi Irc]

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Accession No: DL029792