Introduction to machine learning /
Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of this title reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online)....
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| Format: | Book |
| Language: | English |
| Published: |
Cambridge, Massachusetts :
MIT Press,
[2014]
Cambridge, Massachusetts : The MIT Press, [2014] |
| Edition: | Third edition |
| Series: | Adaptive computation and machine learning
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| Subjects: |
Table of Contents:
- Introduction
- Supervised learning
- Bayesian decision theory
- Parametric methods
- Multivariate methods
- Dimensionality reduction
- Clustering
- Nonparametric methods
- Decision trees
- Linear discrimination
- Multilayer perceptrons
- Local models
- Kernel machines
- Graphical models
- Brief contents
- Hidden markov models
- Bayesian estimation
- Combining multiple learners
- Reinforcement learning
- Design and analysis of machine learning experiments