机器学习的综合基础(Machine Learning——A Comprehensive Foundation)
- ISBN:9787560660547
- 装帧:一般胶版纸
- 册数:暂无
- 重量:暂无
- 开本:其他
- 页数:200
- 出版时间:2021-08-01
- 条形码:9787560660547 ; 978-7-5606-6054-7
本书特色
系统阐述机器学习的思想、技术与方法 注重回答为什么学、从哪里学、学什么、怎么学、学好了吗以及学习意味着什么等机器学习的核心基础问题 全面培养学生的人工智能和大数据处理能力
内容简介
This book provides a comprehensive foundation of machine learning. To answer the questions of what to learn, how to learn, what to get from learning, and how to evaluate, as well as what is meant by learning, the book focuses on the fundamental basics of machine learning, its methodology, theory, algorithms, and evaluations, together with some philosophical thinking on comparison between machine learning and human learning for machinery intelligence. The book is organized as follows: Introduction (Chapter 1), Evaluation (Chapter 2), Supervised learning (Chapters 3, 4, and 5), Unsupervised learning (Chapter 6), Representation learning (Chapter 7), Problem decomposition (Chapter 8), Ensemble learning (Chapter 9), Deep learning (Chapter 10), Application (Chapter 11), and Challenges (Chapter 12). The book can be used as a textbook for college, undergraduate, graduate and PhD students majored in computer science, automation, electronic engineering, communication, ect. It can also be used as a reference for readers who are interested in machine learning and hope to make contributions to the field.
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