A one-stop for unsupervised learning algorithms implemented from scratch in python.
This repository is meant to be a place to study algorithms thoroughly and learn how to implement the theoretical concept. While there are libraries available like scikit-learn which can be used to import implementable models, using them can lead to a gap in understanding of the algorithm itself.
Take the time, learn your algorithm and code!
This repository is specfically for unsupervised learning algorithms only. These algorithms are usually used to solve two types of problems:
- Clustering: Finding structures or patterns in a collection of uncategorized data.
- Association: Discovering rules which describe relationships in your data.
Some examples of the type of algorithms which can be added here:
- K-means
- Hierarchical clustering
- PCA
- Create an issue with details about the algorithm you are implementing.
- Clone the master repository
git clone https://github.com/sashrika15/Unsupervised_Learning_Algorithms.git
- Create your own branch
git checkout -b <branch-name>
- On your branch, create a folder with the name of your algorithm and code!
- Don't forget to help others out by adding a README.md with details of the algorithm you implemented
- Create a pull request once you're done