Perceptron: Part 2Covers the Perceptron algorithm and its application to binary classification problems, including the Pocket Perceptron algorithm.
Dimensionality ReductionIntroduces artificial neural networks and explores various dimensionality reduction techniques like PCA, LDA, Kernel PCA, and t-SNE.
Statistical Physics of LearningOffers insights into the statistical physics of learning, exploring the relationship between neural network structure and disordered systems.
Neural Networks for NLPCovers modern Neural Network approaches to NLP, focusing on word embeddings, Neural Networks for NLP tasks, and future Transfer Learning techniques.