WnCC - Seasons of Code
Seasons of Code is a programme launched by WnCC along the lines of the Google Summer of Code. It provides one with an opprtunity to learn and participate in a variety of interesting projects under the mentorship of the very best in our institute.
List of Running Projects
- Browser Based PDF manager
- Resume Script Generator
- Physicc : A Simple Physics Engine
- Image Colorization
- Language Model Based Syntax Autocompletion in a Text Editor
- Computer vision based web app
- Cribbit Cribbit (Open for PGs Only)
- Techster Texter
- Language Detection
- Book Tracker
- ResoBin - Not the bin we deserve but the bin we need!
- Agree to disagree
- Watson (World's smartest assistant in your pocket)
- Meta Learning - Learning to Learn
- Break free of the matrix, by building one!
- Procedurally Generated Infinite Open World
- Introduction to App Development
- PAC MAN
- Introduction to Web Development
- Goal ICPC
- Traffic congestion modelling and rendering
- Tools for Data Science
- Machine Learning Based Metropolitan Air Pollution Estimation
- Audio controlled drone
- NLPlay with Transformers
- DIY FaceApp
- A Deep Dive into CNNs
- Competitive Coding
- Snake AI
- Facial Recognition App
- Gaming meets AI !!!
- R(ea)L Trader
- Computational Geometry
- Deep reinforcement learning - 2048 AI
- Reinforcement Learning to Finance
- Developing Hybrid ANN-Statistical Model for Robust Stock Market Prediction
- Astronomical Data-modelling and Interpretation
- Visual Perception for Self Driving Cars
- Convolutional Neural Networks and Applications
- Quantum Computing Algorithms
- Algorithm Visualizer
- Anime Club IITB Website using Django
- Machine Learning in Browser
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!
|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|