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Andres Mendez-Vazquez

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2.03 bayesian estimation
05 linear transformations
01.04 orthonormal basis_eigen_vectors
01.03 squared matrices_and_other_issues
01.02 linear equations
01.01 vector spaces
06 recurrent neural_networks
05 backpropagation automatic_differentiation
01 Introduction to Neural Networks and Deep Learning
25 introduction reinforcement_learning
20 k-means, k-center, k-meoids and variations
18.1 combining models
17 vapnik chervonenkis dimension
Schedule for Data Lab Community Path in Machine Learning
Introduction to logistic regression