From Data Preprocessing to Advanced Machine Learning Model's templates with clean Implementation using Python, Jupyter Notebook.
In this repo, I've put several machine learning models that are most widely used as Recipes/Templates for Quick Reference, implementation using Python as .ipnyb files (Jupyter Notebook).
Sometimes we don't notice that ML models use several times the same approach, that can change depending on the data that we have available and the model we want to apply.
In this repo you can find the most known/important ML models and it's implementation for:
- 01 - Data Preprocessing
- 02 - Regression
- 03 - Classification
- 04 - Clustering
- 05 - Association Rule Learning
- 06 - Reinforcement Learning
- 07 - Natural Language Processing
- 08 - Deep Learning
- 09 - Dimensionality Reduction
- 10 - Model Selection & Boosting
All the models are committed as individual folders. The code is always commented and you can also find some sample to test out each approach.