Machine Learning Foundations

Machine Learning Foundations
Author :
Publisher : Springer
Total Pages : 391
Release :
ISBN-10 : 303065902X
ISBN-13 : 9783030659028
Rating : 4/5 (028 Downloads)

Book Synopsis Machine Learning Foundations by : Taeho Jo

Download or read book Machine Learning Foundations written by Taeho Jo and published by Springer. This book was released on 2022-02-13 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists of four parts: foundation, supervised learning, unsupervised learning, and advanced learning. The first part provides the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms. The second and the third parts provide understanding of the supervised learning algorithms and the unsupervised learning algorithms as the core parts. The last part provides advanced machine learning algorithms: ensemble learning, semi-supervised learning, temporal learning, and reinforced learning. Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning; Outlines the computation paradigm for solving classification, regression, and clustering; Features essential techniques for building the a new generation of machine learning.


Machine Learning Foundations Related Books

Foundations of Machine Learning
Language: en
Pages: 427
Authors: Mehryar Mohri
Categories: Computers
Type: BOOK - Published: 2012-08-17 - Publisher: MIT Press

GET EBOOK

Fundamental topics in machine learning are presented along with theoretical and conceptual tools for the discussion and proof of algorithms. This graduate-level
Machine Learning Foundations
Language: en
Pages: 391
Authors: Taeho Jo
Categories: Technology & Engineering
Type: BOOK - Published: 2022-02-13 - Publisher: Springer

GET EBOOK

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists
Deep Learning for Coders with fastai and PyTorch
Language: en
Pages: 624
Authors: Jeremy Howard
Categories: Computers
Type: BOOK - Published: 2020-06-29 - Publisher: O'Reilly Media

GET EBOOK

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with
Deep Learning Illustrated
Language: en
Pages: 725
Authors: Jon Krohn
Categories: Computers
Type: BOOK - Published: 2019-08-05 - Publisher: Addison-Wesley Professional

GET EBOOK

"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magi
Foundations of Machine Learning, second edition
Language: en
Pages: 505
Authors: Mehryar Mohri
Categories: Computers
Type: BOOK - Published: 2018-12-25 - Publisher: MIT Press

GET EBOOK

A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machin