Topics
The Learning Problem
Understanding the Vapnik framework and the learning problem formulation.
Linear Regression
Extracting non-linear patterns with linear models.
Entropy
Information theory principles and their applications.
SGD & Optimization
Stochastic gradient descent and optimization techniques.
Classification Intro
Introduction to classification problems.
The Neuron (Perceptron)
The perceptron algorithm, the fundamental building block of neural networks.
Logistic Regression
Binary classification with logistic regression.