Implementations and Applications of Machine Learning

Saad Subair

• 25 april 2020
• 9783030378295

Samenvatting:

This book provides step-by-step explanations of successful implementations and practical applications of machine learning. deep convolutional neural networks with performance enhancement techniques (including network design, learning rate optimization, data augmentation, transfer learning);

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.

• Presents practical, useful applications of machine learning for practitioners, students, and researchers
• Provides hands-on tools for a variety of machine learning techniques
• Covers evolutionary and swarm intelligence, facial and image recognition, deep learning, data mining and discovery, and statistical techniques