Basic Machine learning from scratch 💻✨

This repository contains implementations of popular machine learning algorithms using Python from scratch. Emphasis is placed on how they are implemented and you can find more efficients implementations of them in popular machine learning libraries such as sckit-learn ⭐

Regression Algorithms 📈:

• Linear Regression
• Polynomial Regression
• Ridge Regression (L2 Regularization)

Classification Algorithms 🔤:

• Perceptron
• Logistic Regression
• Softmax Regression
• K-Nearest Neighbor

Tree based Algorithms 🌲:

• Decision Tree
• Bagging Decision Tree
• Random Forest

Clustering Algorithms 🔤:

• K-Means

Techniques and Machine learning concepts 🌟:

• Overfitting

Feedback

If you have a favourite algorithm that is missing or you spot a mistake in any of the notebook, please let know by creating a new issue

Licence

See the LICENSE file for license rights and limitation (MIT)