Math
Machine Learning
Ranking Problems
Reinforcement Learning
Differential Geometry
Extra content
Datasets
Bias and Variance
Understanding regularization
Laplace approximation
Computing Hessian and Jacobian
Counter factual model
Intro do Manifold Learning
Manifold Learning - Multidimensional Scaling
Active learning
Expectation maximization algorithm - k-means
Data loader example
Neural Network as an Universal Approximator
Variational Autoencoder
