Implementations and Applications of Machine Learning
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Beschreibung
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
Presents practical, useful applications of machine learning for practitioners, students, and researchers
Provides on hands-on tools for a variety of machine learning techniques
Covers clustering algorithms, swarm intelligence, deep learning, and power grid control
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
Autor*in
Saad Subair
Themen in »Implementations and Applications of Machine Learning«
Machine learning Neural networks Support Vector Machines Soft Computing Association Rules Data Mining bioinformatics Health Informatics Emerging technologies in developing countries Emerging technologies complexity