Table of Contents
- Journey from Statistics to Machine Learning
- Parallelism of Statistics and Machine Learning
- Logistic Regression vs. Random Forest
- Tree-Based Machine Learning models
- K-Nearest Neighbors & Naïve Bayes
- Support Vector Machines & Neural Networks
- Recommendation Engines
- Unsupervised Learning
- Reinforcement Learning
