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
- KontaKt App
- Sudoku Spoiler
- GLSL Raytracing
- Decentralized Land Registration on Ethereum
- Galactic Collision Simulator
- Competetive coding
- The Unreasonable Effectiveness of Recurrent Neural Networks
- Generating a human pose dataset using PC games
- Monte Carlo Path Tracing Renderer
- Tabbing App
- Geo-location Augmented Reality
- AR chess app
- Prevention of Sophisticated DoS attack / Network Security
- Winning a Deep Learning challenge
- Automated Fiducial Localisation from MRI/CT Images
- Panorama in Cam Scanner
- 3D Object Reconstruction from Single Image
- Statistical Modelling of Star Maps
- Face Recognition Systems
- Competitive Coding
- Can Machines Identify Genres?
- Joint Modelling of Source Code and Natural Language
- Front end development for FOSSEE websites
- Institute Delivery System
- Capture The Swag
- Panorama in Cam-Scanner
- Poisson Solver with Image Editing
- Blind Source Separation
- FAQ Bot for Freshmen
- Capturing semantic structures in Neural Machine Translation
This project is mostly aimed towards people who are interested in machine learning and involves the use of machine learning algorithms to identify the various music genres
One of the things we, humans, are particularly good at is classifying songs. In just a few seconds we can tell whether we’re listening to Classical music, Rap, Blues or EDM. However, this task is one which computers have historically haven’t been able to solve well. We aim to develop a machine learning algorithm which automatically classifies a song into its correct genre.
The mentee would be expected to work with cutting edge machine learning algorithms to improve the classification of genres. This would require exploratory data analysis, feature selection (which features are relevant towards identification of genres) and implementation of machine learning algorithms to best classify the data.
Get familiarized with the basics of machine learning. One of the excellent resources to kick-off your machine learning journey would be this excellent course offered by Andrew Ng on Coursera
Your proposal should include your experience with machine learning, programming in python (or any standard language) and other relevant projects. It should also include a rough timeline of what you aim to achieve at the end of 2 months.
|Coursera Machine Learning Course||https://www.coursera.org/learn/machine-learning|