Seasons Of Code

Agree to disagree    • Anirudh Mittal,Siddesh Pawar, Pranav Jeevan   

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

Agree to disagree

Agree to disagree


We propose a Harvey-your own lawyer as a browser extension that will read the document for you and summarize the important points in simple language that actually matter to you and which you might want to consider before signing up.

No. of mentees: 6

Description:

How often do you read the terms and conditions before actually signing up for something, installing a software or entering a website? According to a study XX% of internet users don’t. The reason behind that shouldn’t be very hard to find. The Terms and conditions are usually many pages long filled with legal jargon and complex sentences. But can’t we now, with the advancement of technology, find a solution to fix this problem which started 20 years back with the internet in the early 2000s? we propose a Harvey-your own lawyer as a browser extension that will read the document for you and summarize the important points in simple language that actually matter to you and which you might want to consider before signing up.

We’re looking for team members who have some experience with programming. You will have to learn how to collect data, clean it and train ML models on it. If you have any such relevant experience, do mention it in your proposal. Brownie points is you’re interested in law, contracts or policy making.

Tentative Project Timeline

Week Number Tasks to be Completed
Week 1-2 Basics of machine learning and webscraping
Week 3-4 Data collection and browser extension
Week 5 Data preprocessing
Week 6 Traning the model
Week 7 Finetuning the model
Week 8 Implementation

Checkpoints:

Checkpoint Number Progress
1 Learning phase
2 Data and browser extension
3 Preprocessed data
4 Trained model
5 Final product