Implementations and Applications of Machine Learning (1st ed. 2020) (Studies in Computational Intelligence #782)

Synopsis

This book provides step-by-step explanations of successful implementations and practical applications of machine learning. The book’s GitHub page contains software codes to assist readers in adapting materials and methods for their own use. A wide variety of applications are discussed, including wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data mining; and data discovery. Numerous state-of-the-art machine learning techniques are employed (with detailed explanations), including biologically-inspired optimization (genetic and other evolutionary algorithms, swarm intelligence); Viola Jones face detection; Gaussian mixture modeling; support vector machines; deep convolutional neural networks with performance enhancement techniques (including network design, learning rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining; binary classification; and dynamic programming. This book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and teachers in the field of machine learning.

Copyright:

2020

Book Details

Book Quality:

Publisher Quality

ISBN-13:

9783030378301

Related ISBNs:

9783030378295

Publisher:

Springer International Publishing

Date of Addition:

05/02/20

Copyrighted By:

Springer

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Science, Computers and Internet, Technology, Medicine, Communication

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.

Edited by:

Saad Subair

Edited by:

Christopher Thron