Machine Learning By Zhi-Hua Zhou
Material type: TextPublication details: Singapore: Springer, 2021Edition: 1Description: i-xiii+458PISBN:- 9789811519697
- 1 006.31
Item type | Current library | Home library | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|
Book | Dept. of Computational Biology and Bioinformatics | Dept. of Computational Biology and Bioinformatics | 006.31 ZHO-M (Browse shelf(Opens below)) | Checked out to Ann (COB230504M) | 23/05/2024 | DCB4314 |
This textbook offers a comprehensive and unbiased introduction to almost all aspects of machine learning, from the fundamentals to advanced topics. It consists of 16 chapters divided into three parts: Part 1 (Chapters 1-3) introduces the fundamentals of machine learning, including terminology, basic principles, evaluation, and linear models; Part 2 (Chapters 4-10) presents classic and commonly used machine learning methods, such as decision trees, neural networks, support vector machines, Bayesian classifiers, ensemble methods, clustering, dimension reduction and metric learning; Part 3 (Chapters 11-16) introduces some advanced topics, covering feature selection and sparse learning, computational learning theory, semi-supervised learning, probabilistic graphical models, rule learning, and reinforcement learning. Each chapter includes exercises and further reading, so that readers can explore areas of interest.
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