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
This project aims to introduce use of Convolutional Neural Networks which is the state-of-the-art technique for various image-based machine learning problems.
No. of mentees:8
We will cover the basic idea and theory behind the CNNs and implement it for two different projects. We are considering an image classification project and an image processing project for implementation, but the implementation projects are not fixed and can be changed later based on time constraints, mentees’ capabilities and other factors.
Prior exposure to python is recommended (not much different from C++ you learned in CS101). You will be introduced to various libraries often used for data processing and machine learning. Apart from these tools, we will cover the structure and implementation of CNN from basics and will provide resources related to the topic.
We have selected two sub projects based on CNN. You will be assigned to one of them after you are comfortable with the basics of the topic and implementation. As far as the proposal is concerned, you should mention your previous exposure to python and machine learning techniques (if any). Also if you have any prior coding project experiences(any language and domain), you can mention them. We also won’t mind some coding puns in your proposal, although that won’t be associated with your selection :p.
Image Super Resolution Via CNN : For this, we attempt to improve the resolution of low resolution patches in a given image which may have arisen due to faulty imaging hardware or software degradation.
Predicting Genre from Movie Posters: To train and create a model to learn features from movies’ posters and to predict the genre of the movie it represents with high probability.
Tentative Project Timeline
|Week Number||Tasks to be Completed|
|Week 1-2||Understanding the basics of ML like Linear Regression, Logistic Regression, Neural Networks, etc..|
|Week 3||Learning about Convolutional Neural Networks and their applications|
|Week 4||Getting familiar with implementation of neural networks and CNNs in python using Tensorflow/ Keras|
|Week 5||Understanding the architecture of project models, their implementation and training.|
|Week 6||Testing, Further improvements and Report|