Section outline
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Κύρια textbooks
- Simon Haykin - Neural Networks and Learning Machines - Prentice Hall, 3rd Edition (2008) - Simon Haykin, Νευρωνικά Δίκτυα και Μηχανική Μάθηση, Εκδόσεις Παπασωτηρίου, 2010 (διανέμεται στο πλαίσιο του μαθήματος)
- Κωνσταντίνος Διαμαντάρας, Τεχνητά Νευρωνικά Δίκτυα, Εκδόσεις Κλειδάριθμος, 2007 (διανέμεται στο πλαίσιο του μαθήματος)
Συμπληρωματικά textbooks
- John A. Hertz, Anders S. Krogh, Richard G. Palmer - Introduction To The Theory Of Neural Computation - Westview Press (1991)
- Michael Negnevitsky - Artificial Intelligence A Guide to Intelligent Systems - Addison Wesley, Second Edition (2005)
- Martin T Hagan, Howard B Demuth, Mark H Beale, Orlando De Jesús - Neural Network Design (2nd Edition) 2014
- Raul Rojas - Neural Networks A Systematic Introduction - Springer (1996) (available online)
- Ian Goodfellow and Yoshua Bengio and Aaron Courville - Deep Learning - MIT Press (2016) (available online)
- Zhang, A., Lipton, Z. C., Li, M., & Smola, A. J. - Dive into deep learning - (2020) (available online)
Άρθρα
- Coolen, Anthony CC. "A beginner’s guide to the mathematics of neural networks." In Concepts for Neural Networks, pp. 13-70. Springer, London, 1998. (available online)
- Jain, Anil K., Robert P. W. Duin, and Jianchang Mao. "Statistical pattern recognition: A review." IEEE Transactions on pattern analysis and machine intelligence 22, no. 1 (2000): 4-37. (available online)
Βιβλιοθήκες
- scikit-learn (machine learning)
- somoclu (competitive learning)
- deap (evolutionary algorithms)
- keras (deep learning)
- tensorflow (deep learning)
- stable-baselines3 (reinforcement learning)
Αντιστοίχιση διαλέξεων - κεφαλαίων βιβλιογραφίας
Διαλέξεις Haykin Διαμαντάρας Hertz Negnevitsky Hagan Rojas Goodfellow Dive Gradient Descent 4 8 11 Perceptron - MLP 1,4 2,3 5,6 6 4,11 4,6,7 4 SVM 6 4 Hebbian Learning, Hopfield Model 13 7,8 2 21,15 12,13 Competitive Learning 9 16 SOM 9 9 8 Reinforcement Learning 12 7 Genetic Algorithms 7 17 Combinatorial Optimization 4,7 14 Deep Learning 6 5 Convolutional NN 9 6,7 Recurrent NN 15 10 8 Autoencoders & GAN 14 17