Implementations and Applications of Machine Learning

Saad Subair (Curatore)

Christopher Thron (Curatore)

Springer Nature Switzerland AG, 2020

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.

• Curatore: Saad Subair, Christopher Thron
• Editore: Springer Nature Switzerland AG
• Collana: Studies in Computational Intelligence
• Anno: 2020
• Rilegatura: Hardback
• Pagine: 280 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783030378295

Testo in English