Machine Learning (Supervised)
Chapters
Chapters
Ch 1. Introduction and Evaluation Metrics
Ch 2. Regression Models
Simple Linear Regression
Multiple Linear Regression
Ridge Regression
Ch 3. Classification Model I
Logistic Regression
k-Nearest Neighbors
Naive Bayes
Ch 4. Classification Models - II
Fisher's LDA
LDA, QDA & Decision Boundaries
Ch 5. Model Evaluation and Generalization
Ch 6. Regression and Classification Models
Decision Trees
Support Vector Machines
Neural Networks
Chapter 3: Classification Model I - Logistic Regression
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Machine Learning (Supervised)