GreyAtom’s Program in Data Science gives you the opportunity to work on real industry datasets. We encourage our enrollees to build models that create value for the employer. Feel free to peruse through the projects portfolio to see the kind of impact GreyAtom students make.

My model, based on data from marketing campaigns of a Portuguese bank, predicts whether clients will subscribe for term deposits.

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Classifier for a Portuguese bank

Presentation

Rahul Jain

Student @ GreyAtom | Working with Shoppers Stop

My research aimed at comparing predictive accuracy of data mining methods for credit card default in the Taiwanese demographic.

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Model for predicting credit card default

Git

Sandip Baradiya

Student @ GreyAtom | Working with Coverfox

My goal was to build predictive model of factors that influence a client’s decision to subscribe to term deposits.

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Analysis of subscription for term deposit

Code

Nikhil Akki

Student @ GreyAtom | Working with Deloitte

We used fuzzy features and word2vec to identify duplicate questions on Quora.

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Quora Duplicacy Identifier

Presentation

Group Project: Team Dolphin

Students @ GreyAtom

Sharad S., Ketan C., and 3 more.

We used the feature of cosine similarity combined with random forest to weed out duplicate questions on Quora.

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Find Quora Redundancies

Presentation

Group Project: Team Blue Whale

Students @ GreyAtom

Srishti S., Amrinder B., and 3 more.

We applied different techniques to analyze panel data and come out with the forecast for multiple time series.

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Trade Forecasting

Prezi

Group Project: Team Shark

Students @ GreyAtom

Charulata Shelar

Our team tried a new approach called Multi-View ML and we were able to increase the accuracy of predictions for credit card defaults.

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Credit Card Default Identifier

Prezi

Group Project: Team Seahorse

Students @ GreyAtom

Chinmay Chopade

We applied random forest algorithm to predict the bankruptcy of a company.

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Bankruptcy Calculator

Presentation

Group Project: Team Walrus

Students @ GreyAtom

Aditya, Aman, and 4 more.

Our goal was to predict if the client will subscribe to the bank’s term deposit through the campaign based on calls.

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Marketing Campaign Analysis

Presentation

Group Project: Team Sealion

Students @ GreyAtom

 

Our team extracted various features out of credit card default data to improve predictions.

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Improving CC Default Predictions

Presentation

Group Project: Team Seashells

Students @ GreyAtom

Vinayak K., Amrinder B., and 5 more.

We applied linear regression to a time series data for trade forecasting.

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Forecasting Stocks

Presentation

Group Project: Team Jellyfish

Students @ GreyAtom

Anup B., Amol D, and 3 more.

Given a tweet from the user, automatically detect whether the tweet is sarcastic based on the previous tweets from the same user.

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Sarcasm Detection

Presentation

Group Project: Team Seal

Students @ GreyAtom

Aditya S., Sanchita H. and Noorain R.

Implement a machine learning solution to identify watch patterns in specific customer segments

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Segment detection for Hotstar

Presentation

Group Project: Team Oyster

Students @ GreyAtom

Swapnil C., Kishan E., Neeha K. and Calvin C.

Built a machine learning model that, given a tweet, can classify it correctly as sarcastic or non-sarcastic.

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Segment Detection

Presentation

Group Project: Team Tuna

Students @ GreyAtom

Hardika B., Naitik G., and Aishwarya K.