An Introduction to Machine Learning
This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, lin...
| Published in: | Springer eBooks |
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| Format: | eBook |
| Language: | English |
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Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Online Access: | http://dx.doi.org/10.1007/978-3-319-20010-1 Перейти в каталог НБ ТГУ |
Table of Contents:
- A Simple Machine-Learning Task
- Probabilities: Bayesian Classifiers
- Similarities: Nearest-Neighbor Classifiers
- Inter-Class Boundaries: Linear and Polynomial Classifiers
- Artificial Neural Networks
- Decision Trees
- Computational Learning Theory
- A Few Instructive Applications
- Induction of Voting Assemblies
- Some Practical Aspects to Know About
- Performance Evaluation.-Statistical Significance
- The Genetic Algorithm
- Reinforcement learning.