Machine Learning an algorithmic perspective
Introduction. Linear Discriminants. The Multi-Layer Perceptron. Radial Basis Functions and Splines. Support Vector Machines. Learning with Trees. Decision by Committee: Ensemble Learning. Probability and Learning. Unsupervised Learning. Dimensionality Reduction. Optimization and Search. Evolutionary...
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| Format: | eBook |
| Language: | English |
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Boca Raton, FL
CRC Press
2015
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| Edition: | Second edition |
| Series: | Chapman & Hall/CRC machine learning & pattern recognition series
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| Subjects: | |
| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- Introduction
- Preliminaries
- Neurons, neural networks, and linear discriminants
- The multi-layer perceptron
- Radial basis functions and splines
- Dimensionality reduction
- Probabilistic learning
- Support vector machines
- Optimisation and search
- Evolutionary learning
- Reinforcement learning
- Learning with trees
- Decision by committee: ensemble learning
- Unsupervised learning
- Markov chain Monte Carlo (MCMC) methods
- Graphical models
- Symmetric weights and deep belief networks
- Gaussian processes
- Python
- Includes bibliographical references