Linear Regression with one and multiple variables, Gradient Descent and Cost Function, Linear Algebra, Logistic Regression, Regularization, Multiclass Classification, Solving the Problem of Overfitting, Neural Networks and Backpropagation, Evaluating a Learning Algorithm, Bias vs. Variance, Support Vector Machines, Unsupervised Learning, Dimensionality Reduction, Anomaly Detection, Recommender Systems, Density Estimation, Multivariate Gaussian Distribution, Collaborative Filtering, Low Rank Matrix Factorization, Gradient Descent with Large Datasets, Photo OCR.
