Machine-Learning

Machine Learning models implementations with Python and R.

Topics and Contents

This repo contains several topics, mainly in models of Machine Learning, including:

1. Data Preprocessing
2. Regression
3. Classification
4. Clustering
5. Association Rule
6. Reinforcement Learning
7. Natural Language Processing
8. Deep Learning
9. Dimensionality Reduction
10. Model Selection

There are some small datasets to experiment on, also some documentations and self-taken notes in it.

Environment

This code is purposely made in Spyder IDE so it contains #%% to make notebook cells. Why Spyder?

1. Convenient and Practical
2. All-Rounder IDE
3. Cool and Adaptive Design

Reference

Machine Learning A-Z

Notes

• There are some intentionally left empty parts in the source codes to be filled with entries needed later.
• Make sure to download and install libraries needed for the computational processes in Spyder IDE.