Machine Learning Notebook

This Repo documented 10+ machine learning and deep learning algorithms and general ML concepts with detailed explanations of underlying mathematical principles, theoretical insights, and implementation techniques, offering a clear understanding of their mechanisms, use cases, and performance optimization strategies. It servers as my personal study notes, and also an educational resource for those who wish to deepen their knowledge in the field

Content

1. Linear regression
2. Classification
3. Clustering (K-means)
4. Naive bayes
5. Decision trees
6. Principle component analysis (PCA)
7. Neural networks
8. Recommender systems
9. Anomaly detection
10. Reinforcement learning
11. Convolutional neural network (CNN)
12. NLP
13. Generative adverserial networks (GAN)
14. VAEs
15. Diffusion model
16. Concepts & Guilds: includes evalution methods and ML best practices