- Single-Layer Networks
- Multi-Layer Networks
- Error Functions
- Weights Optimization Algorithms and Regularization
- Hopfield Network
- Boltzmann Machine
- Winner Take All Neural Network (Unsupervised Learning)
- Evolving Neural Networks
- Comparison to Support Vector Machine
| Topics & slides | Lecture date: |
|---|---|
| Introduction to Neural Computation & Optimization, Single-Layer Networks, Lecture 1 (PDF), Lecture 1 (PS.GZ) | 04.04.2008 |
| Bayesian Decision, Perceptron, LMS, Lecture 2 (PDF), Lecture 2 (PS.GZ)(revised) | 11.04.2008 |
| Multi-Layer Networks, Backpropagation, Lecture 3 (PDF), Lecture 3 (PS.GZ) | 18.04.2008 |
| Regularization, Over/Underfitting, Momentum, Lecture 4 (PDF), Lecture 4 (PS.GZ) | 25.04.2008 |
| Learning Rate, Hopfield Network, Lecture 5 (PDF), Lecture 5 (PS.GZ) | 09.05.2008 |
| Boltzmann Machine, Lecture 6 (PDF), Lecture 6 (PS.GZ) | 16.05.2008 |
| PCA (with Neural Networks), Feature Extraction, Lecture 7 (PDF), Lecture 7 (PS.GZ) | 30.05.2008 |
| Winner-Take-All, K-Means, SOM, Lecture 8 (PDF), Lecture 8 (PS.GZ) | 06.06.2008 |
| Evolving Neural Networks, Lecture 9 (PDF), Lecture 9 (PS.GZ) | 13.06.2008 |
| Support Vector Machine, Lecture 10 (PDF), Lecture 10 (PS.GZ) | 20.06.2008 |
| Neural Networks for Time Series Prediction, Support Vector Regression, Lecture 11 (PDF), Lecture 11 (PS.GZ) | 27.06.2008 |
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Neural Networks for Pattern Recognition, Christopher M. Bishop, Oxford University Press, 1995, ISBN: 0198538642 |
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Neural Networks: A Comprehensive Foundation (2nd Edition), Simon Haykin, Prentice Hall Publishers, 1998, ISBN: 0132733501 |
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Introduction to the Theory of Neural Computation, John Hertz, Andreas Krogh, Richard Palmer, Addison Wesley, 1991, ISBN: 0201515601 |
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Information Theory, Inference and Learning Algorithms, David MacKay, Cambridge University Press, 2003, ISBN: 0521642981 |
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Single Layer Network (Perceptron, LMS, Pseudoinverse), Lecture 1 & 2, download  source code (single.layer.nn.R)
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Network Output as Posterior Probability, Lecture 1 & 2, download source code (logistic.discr.R)
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Multi-Layer Network, Decision Regions, Lecture 3, download source code (multi.layer.nn.R)
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Momentum, Lecture 4, download source code (rosenbrock.function.momentum.R)
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Hopfield Network, Lecture 5, download source code (hopfield.network.R)
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PCA, Oja's update rule, Lecture 7, download source code (PCA.Oja.R)
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PCA example (projection + reconstruction), Lecture 7, download source code (PCA.image.R,charly.pgm)
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Winner-Take-All, Lecture 8, download source code (WTA.R)
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Support Vector Machine, Lecture 10, download source code (SVM.R)
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Modern Applied Statistics with S (4th Edition), W.N. Venables, B.D. Ripley, Springer-Verlag, 2002, ISBN: 0387954570, (Note: this book covers also R). |
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Programmieren mit R (Statistik und ihre Anwendungen) (2. Auflage), Uwe Ligges, Springer-Verlag, 2006, ISBN: 3540363327 |