Book Details
Format
Hardback or Cased Book
Book Series
Springer Series in the Data Sciences
ISBN-10
3030395677
ISBN-13
9783030395674
Edition
2020 ed.
Publisher
Springer Nature Switzerland AG
Imprint
Springer Nature Switzerland AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
May 16th, 2020
Print length
582 Pages
Weight
1,024 grams
Dimensions
16.10 x 24.30 x 4.00 cms
Product Classification:
OptimizationMachine learning
Ksh 21,600.00
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This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms.
This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.
Get First-order and Stochastic Optimization Methods for Machine Learning by at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Springer Nature Switzerland AG and it has pages.
