Seasons Of Code

Why The Hype Around GANs    • Akshit Srivastava, Tezan Sahu   

Why The Hype Around GANs

Why The Hype Around GANs

Yann LeCun described GANs as “the most interesting idea in the last 10 years in Machine Learning”. And, indeed, Generative Adversarial Networks (GANs for short) have had a huge success since they were introduced in 2014 by Ian J. Goodfellow.

This project will involve learning many machine learning algorithms leading to GANs. Mentees will implement a Generative Adversarial Network from scratch.

For students who have participated in Summer of Science (Machine Learning track) before, this would be a great hands-on project!

Tentative Timeline:

Week Work
Week 1-2 Learn/Brush-up Python, Torch, Jupyter, Numpy, Unix commands
Week 3-4 Learn Linear Regression, Logistic Regression, Neural Networks
Week 5-6 Read up on the use cases and building blocks of Deep Learning.
Week 7-8 Implement a generative adversarial network from scratch and train it on toy dataset.
Week 9-10 Learn PyTorch/TensorFlow, implement a GAN network using the library.
Week 11-12 Start collecting data and training. Document all interesting observations