Artificial Neural Networks

Code: PINF7061
Course: PhD program in computer science
Credits: 4
Hourly load: 60

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* R. O. Duda, P. E. Hart, D. G. Stork, "Pattern Recognition and Scene Analysis 2.ed.", Wiley, New York, NY (2001)
* A. Géron, "Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems", O'Reilly, 2017
* I. Goodfellow, Y. Bengio, A. Courville, "Deep Learning", MIT Press, 2016
* S. Haykin, "Redes Neurais, Princípios e Prática, 2.ed", Bookman., Porto Alegre, 2002.
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* J. Hertz, A. Krogh, R. Palmer, "Introduction to the Theory of Neural Computation", Addison-Wesley, Redwood City, California, 1991.
* T. Kohonen, "Self-Organization and Associative Memory", Springer-Verlag, Berlin, 1989.
* A. de Pádua Braga, A. Ponce de Leon F. Carvalho, T. Bernarda Ludermir, "Redes Neurais Artificiais - Teoria E Aplicações, 2ª Ed", Editora LTC., 2007.
* Y. H. Pao, "Adaptive Pattern Recognition and Neural Networks", Addison Wesley, Reading, Massachusetts, 1989.
* R. Schalkhoff, "Pattern Recognition, statistical, structural and neural approaches", John Wiley and Sons, New York, 1992.
* V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer,1996.
* H. White, "Artificial Neural Networks: Approximation and Learning Theory", Blackwell, Oxford, 1992.