A little about me

I'm a Btech student based in New Delhi and have a profound interest in data and analytics. I see data as a tool through which a statement becomes a fact and I find that extremely empowering.I love to listen to the oldest of tunes and am a complete bollywood fanatic by heart.

Education

Guru Gobind Singh Indraprastha University (2018 - 2022)
Bachelor's of Technology (Computer Science)

COURSEWORK

  • Algorithms and Data Structures
  • Computer Networks
  • Theory of Computation
  • Computer Organisation and Architecture
  • Software Engineering
  • OOP Programming
  • Software Engineering
  • inear Algebra
  • Discrete Mathematics
  • Operating Systems
  • Compiler Design
  • Database Management Systems

The Srijan School,Model Town(2017 -2018)
Class 12 (Science)

Sunrise English Private School,Abu Dhabi, UAE(2015 -2016)
Class 10

Internships and Volunteering Experience

HackerRank
Product Analyst Intern(May 2021- Present)

Ideate, develop and maintain new and ongoing metrics, reports and dashboards to support business needs and transform business needs into data collection and data analytics processes.

Aztlan
Data Scientist (August 2020 - December 2020)

Scrapped, cleaned and analysed data and performed basic modelling for the same.

TechForGood (Volunteering)
GirlsxTech Champion (August 2020)

Tech For Good aims to bridge the gender gap in technology by training 50,000 women with tech education programs by 2025.

Projects

Credit Card Fraud Detection

In this project I build machine learning models to identify fraud in European credit card transactions. I also make several data visualizations to reveal patterns and structure in the data.I was able to accurately identify fraudulent transactions using a random forest model. I also calculated mutual information values to identify the variables most correlated with fraud. On a test set consisting of 20% of the original data, the predictions from the random forest model had an F1 score of 0.869 and a Matthews correlation coefficient (MCC) of 0.869. I also trained logistic regression and linear support vector classifier models, but these models underperformed the random forest. To improve a particular model, I optimized hyperparameters via a grid search with 5-fold cross-validation.

See Project

Fish-Weight-Estimation

The aim of this study is to estimate weight of the fish indivuduals from their measurements through using linear regression model. This study can be improved to use in fish farms. Individual fish swimming in front of the camera can be measured from the video image and the weight of the fish can be estimated through the linear regression model.

See Project

Titanic-Data-Analysis

On April 15, 1912, during her maiden voyage, the widely considered “unsinkable” RMS Titanic sank after colliding with an iceberg. Unfortunately, there weren’t enough lifeboats for everyone onboard, resulting in the death of 1502 out of 2224 passengers and crew. While there was some element of luck involved in surviving, it seems some groups of people were more likely to survive than others. This project is an attempt to determine the survival rates of the people aboard the ship.

See Project

Personal Portfolio

Personal Portfolio built usinh HTML,CSS and JavaScript.

See Project