A Machine Learning repository aiming to cover all popular
- Machine learning algorithms with their explanation
- Commonly used techniques
- Features selection techniques
- Feature extraction techniques
- Evaluation metrices
The motivation behind creating this repository is just to help other growing data scientist understand the core concepts, theories and practical part of machine learning. This repository also aims to help the people in revising the cocepts of machine learning algorithms.
Few examples of the notebook
DBSCAN |
KMeans |
Elbow Method |
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The resources used in algorithm explanation is picked from publicly available website, youtube videos(eg StatQuest), thanks to them. However some of the resources used in this repository is also from my own website, which I created by myself
Don't forget to star it, if it helps 🤑😁
🐱💻 Work in progress 🔥