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 Projects
- Emoji Predictor
- FAQ Bot for Freshmen
- Capturing semantic structures in Neural Machine Translation
- Automated Fiducial Localisation from MRI/CT Images
- 3D Object Reconstruction from Single Image
- Statistical Modelling of Star Maps
- Face Recognition Systems
- Competitive Coding
- Can Machines Identify Genres?
- Monte Carlo Path Tracing Renderer
- Joint Modelling of Source Code and Natural Language
- Panorama in Cam Scanner
- Front end development for FOSSEE websites
- Institute Delivery System
- Capture The Swag
- Panorama in Cam-Scanner
- Poisson Solver with Image Editing
- Blind Source Separation
This project aims at the use of Machine Learning to build an algorithm to find the right emoji.
Problem Statement : Here, we plan on building an efficient algorithm and writing a script for this purpose at the same time maximising the accuracy. Detecting emotions from the facial features and speech have seen several advancements. Text based recognition is an emerging field and uses the latest and cutting edge ML techniques such as recurrent algorithms, sentiment analysis etc. In computational linguistics, this problem is becoming increasingly useful from the application perspective. The biggest challenge in this field is context-dependence of emotions within text.
A mentee, by the end of the project is expected to get comfortable with handling and tinkering around with several related libraries of Python and certain basic concepts related to this field of Machine Learning.
Proposal : You are expected to mention your familiarity with Machine Learning and other fields which include Linear Algebra and probability theory apart from your motivation in the project proposal. Also, experience with Python programming. Note that these are not the pre-requisites.
To get a better insight into the specifics of the project and other related details, I suggest you take a look at the dataset and the references posted here. Also, to start off with basic Machine Learning you can go through Andrew Ng’s notes or the course on Coursera. Though, you will be learning on the go.