ML Notes
Welcome! This site is a collection of personal notes on machine learning concepts, featuring Python implementations of fundamental neural network layers and architectures, as well as summaries of key research papers. It is designed as a resource for both theoretical understanding and practical coding exercises.
Table of Contents
- Fundamentals
- Weight Initializers
- Optimizers
- Regularization
- Convolution
- Max Pooling
- Batch Normalization
- RNN
- LSTM
- Attention
- Tokenization
- Reinforcement Learning
- Models
- Papers
Feel free to explore each section for detailed explanations, mathematical derivations, and code examples.
References: