While learning about machine learning algorithms, I wanted to build them from scratch without importing the complete model from libraries to understand how they work. Within this repository are the models I built:
- General Linear Models(GLMs)
- Naive Bayes
- Decision trees
- Random Forest
- Adaptive Boosting(AdaBoost)
- Gradient boosting trees
- Kmeans clustering