面向智能应用的机器学习混合与优化

English | 2024 | ISBN: 1032737530 | 367 pages | True PDF,EPUB | 63.6 MB

This book discusses state-of-the-art reviews of the existing machine-learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation.

Features • Focuses on hybridization and optimization of machine learning techniques. • Reviews supervised, unsupervised and reinforcement learning using case study based applications. • Covers latest machine learning applications in diverse domains as IoT, data science, cloud computing, distributed and parallel computing. • Explains computing models using real world examples and dataset based experiments. • Includes case study based explanations and usage for machine learning technologies and applications

This book is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering.

英文| 2024 |国际标准图书编号：1032737530 | 367页|真PDF，EPUB | 63.6 MB 本书讨论了现有机器学习技术和算法的最新进展，包括混合和优化。它涵盖了通过人工智能（AI）预测工具进行机器学习的应用、药物的发现、神经科学、多种成像方式的诊断、功能性磁共振成像的模式识别方法、图像和语音识别、自动语言翻译、医学诊断、股票市场预测、交通预测和产品自动化。 特点•专注于机器学习技术的混合和优化。•使用基于案例研究的应用程序对监督学习、无监督学习和强化学习进行审查涵盖了物联网、数据科学、云计算、分布式和并行计算等不同领域的最新机器学习应用使用真实世界的示例解释计算模型

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