Learning-ML

Here I list my progress in studying machine learning.

Table of Content

1. Lectures: Assignments I completed

   • Machine Learning (Coursera, Andrew Ng)
   • CS231n (Stanford)

2. Papers: Reviews and tutorials

   • XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
   • Pytorch Beginner's Tutorial in Jupyter notebook

3. Implementations: Concepts and specific papers

   • Autoencoder (AE), Denoising Autoencoder (DAE)
   • Variational Autoencoder (VAE)
   • Conditional Variational Autoencoder (CVAE)
   • Deep Convolutional GAN (DCGAN)