sunoh-kim / deep-learning

This repository contains my assignment solutions for the Deep Learning course (M2177.003100_002) offered by Seoul National University (Fall 2019).

Deep Learning - Assignment Solutions

This repository contains my assignment solutions for the Deep Learning course (M2177.003100_002) offered by Seoul National University (Fall 2019).

The algorithms for the assignments are implemented using TensorFlow and PyTorch in Python.

Assignment0 (TensorFlow):

Environment Setup, Linear Model

Assignment1 (TensorFlow):

Data Curation, Implementing Neural Networks from Scratch, Neural Networks

Assignment2 (TensorFlow):

Implementing Convolutional Neural Network (CNN), Training CNN, Visualizing CNN

Assignment3 (TensorFlow):

Implementing Recurrent Neural Network (RNN), Image Captioning, Language Modeling

Assignment4 (TensorFlow):

Implementing Variational AutoEncoder (VAE) with MNIST data, Implementing Conditional-Generative Adversarial Network (GAN) with MNIST Data, Implementing Conditional-GAN with Face Data

Assignment5 (TensorFlow):

Implementing and Training a Deep Q-Network (DQN), Playing Atari games using an Asynchronous Advantage Actor-Critic (A3C) agent

Final Project (PyTorch):

Text-to-image Synthesis based on AttnGAN

Reference

@article{Tao18attngan,
  author    = {Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, Xiaodong He},
  title     = {AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks},
  Year = {2018},
  booktitle = {{CVPR}}
}