The field of Machine Learning has become more prevalent throughout the last decade. This repository is for me to keep track of all the papers I read as well as my notes about them. I occasionally implement some of the models and push them up as well.
I appreciate all model implementation contributions as well as bug fixes on the currently existing ones. Feel free to open up issues if there is anything wrong with the current implementations as well.
- A Brief Survey of Deep Reinforcement Learning
- A Deep Convolutional Auto-Encoder with Pooling Unpooling Layers in Caffe
- A Few Useful Things to Know About Machine Learning
- CS231n Notes
- Deep Learning using Linear Support Vector Machines
- Deep Residual Learning for Image Recognition
- Densely Connected Convolutional Networks
- Distilling the Knowledge in a Neural Network
- Introduction to GANS
- Learning to Learn by Gradient Descent by Gradient Descent
- Learning Transferable Architectures for Scalable Image Recognition
- Network In Network