This is the overview of basic and important machine learning models, methods and concepts and theories. I acknowledge all information and knowledge including images, data… I have taken from those two courses: https://www.coursera.org/learn/machine-learning
Our series comprise of following topics:
Section 1: Introduction, Linear regression, Generative and Discriminative Model, Perceptron, Logistic Regression, Naive Bayes and Gaussian Discriminant Analysis (this post). Section 2: Four important Discriminative Models: K-Nearest Neighbors, Support Vector Machine, Decision Tree and Neural Network.