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.