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Full Description
The book aims to develop methodologies and throw light on the advances in empirical research of various machine learning systems through data mining and parallel programming using GPU approaches. It reviews concepts of existing machine learning and deep learning techniques and how these can be implemented in GPU computing with CUDA architecture. The book also discusses modern machine learning techniques for effective big data management in accordance with worldwide standards in the field.
Covering diverse areas, this publication is meant for academicians, data scientists, industrial professionals, researchers and students interested in uncovering the latest innovations in the field.
Contents
Preface. Computation and Analysis for Genome Mapping using the Deep Learning-based Optimization Algorithm. Prediction for Genome Mapping with the Multi-objective Evolutionary Algorithm. Deep Learning and Medical Data Engineering for Knowledge Discovery. Integrating DL Techniques for Precise Genome Mapping: Methods and Applications. Analysing Genomes using Deep Learning and Image Processing Techniques. Introduction to Neural network and Machine Learning as a Subset of AI. Advancing Smart Healthcare: Enhanced Image Analysis and Feature Extraction through Integration of Sharpening Techniques and Edge Detection Algorithms. Optimizing Noise Reduction Strategies in Medical Imaging through Advanced Techniques and Performance Evaluation Metrics. Revolutionizing Medicine: Machine Learning Innovations in Medical Science. Development and Validation of an AI-Based Model for Heart Delineation in Chest X-Ray Images. Index.
