
UFC Fight Classification Model & Blog
A classification project to clean UFC fight data and predict the winner using a Random Forest model with cross-validation. Complete blog & analysis included.
Here you will find more information about my work experience, projects, education background and more!
I was born in Chennai, India, and as a person of mixed descent, I was fortunate to travel the world growing up.
I've lived in several states throughout America as well as different cities in India and Canada. Me ending up here
in Toronto was completely unexpected for us, as we only intended to stay here for a few months, but my ankle had
something else to say about that.
I broke my ankle skateboarding which forced me to stay for a middle school semester back in 2011 and I've been
here in Toronto ever since (and it's not because my ankle is still broken 😅).
I really started to fall in love with Mathematics and data during my final years of highschool and my first few
semesters at university, I find Mathematics to be one of the most challenging and rewarding fields of study that
we can immerse ourselves in and it pushes me every day to be my best self.
Due to my love of Mathematics, I decided to pursue a double major in Mathematics and Statistics at the University
of Toronto, Scarborough for my undergrad focus, a program from which I have graduated with honors in November 2022.
Find the attached pdf and word files for my most up-to-date resume in Data Science.
Click the project title or its thumbnail to view the project in detail. Clicking a Tableau workbook will install the packaged .twbx file.
A classification project to clean UFC fight data and predict the winner using a Random Forest model with cross-validation. Complete blog & analysis included.
This repo contains a Udacity Data Science project that categorizes messages for disaster response purposes through the building, training and implementation of an end-to-end NLP (Natural Language Processing) pipeline along with a companion Flask application.
This project contains a notebook along with a complete Data Science project and analysis to illustrate important concepts from the Udacity Data Science Nanodegree program.
This project uses given parameters of houses in California and their respective prices to create predictive models in a Python Jupyter notebook.
This dashboard utilizes a San Diego real estate dataset to create an interactive real estate poster!
This project uses Toronto and Calgary weather data throughout the years to answer important climate change questions with intuitive visualizations.
This program accesses the Scotts Directories website and uses Python's Selenium web automation library to automatically collect business information.
This program uses ibba.org to collect contact information of business brokers in locations of interest.
Feel free to shoot me an email or give me a call for any questions or just to chat!