Portfolio Website

My name is Aaryaman Singh and I am a undergraduate student at UW Madsion. I am a declared CS major at UW Madison. I like to play videogames, code, workout, and read. Some of my interests are in the fields of Generative AI, Blockchain development and Web 3.0, Computer Vision, Deep Learning, and Cloud Computing. Please explore this website and reach out if you would like to collaborate on future projects. Thanks!

I went to Walton High School in Marietta, Georgia. I took 15 AP courses during my high school career and graduated in May 2022. I am currently at UW Madison (Class of 2026) studying Computer Science. I have been involved in clubs/organizations like Dot Data (Data Science Club), AI Club, and Google Student Developer Club. I am currently junior standing and have taken courses such as CS300, CS400, Discrete Math (MATH/CS 240), Linear Algebra (Math 340), and ECON 101. I am interested in meeting like-minded developers and those with interests in CS-related fields or with business/startup ambitions to collaborate on projects and further grow UW Madison's tech scene. Please feel free to reach out to my contacts below!

Personal Projects

Check out my personal projects below via their links!

Check out my Microsoft Teams Chat App clone built with React JS components for Frontend and ChatEngine.io. for Backend. This project utilized Sockets, Rest APIs, Sending Images, React Hooks, Props, and advanced CSS styling.

Check out my Car-Showcase Website!

Take a look at my car showcase website built with Next.js 13, React.js, TypeScript, TailwindCSS. This project utilizes Next.js 13 App Router and Server-Side Rendering. This Car Showcase Website implements advanced search functionality and optimizes metadata and SEO.

Explore my Machine Learning House Price Prediction Model!

This Machine Learning model was built using Google Collabatory and utilized Python and its relevant libraries such as Numpy, Pandas, ScikitLearn, MatPlotLib, and Seaborn. This project goes through the entire data analysis process of first loading in a data set (Housing Prices from California in 1990), then exploring the data, preprocessing the data, performing feature engineering, and then building a linear regression model and Random Forest model to help predict housing prices with great accuracy.

Take a look at my Stock Price Prediction Model!

This Stock Price Prediction Model project encompasses many different ML techniques as well as models such as Linear Regression, Support vector Machines, and Regularization to accurate predict the stock price of AAPL and the evaluation of these models was done through error metrics such as MSE (Mean-Squared Error) and RMSE (Root Mean Squared Error).

Watch the changes from 1980-2023 in Japan's GDP vs. Nikkei Index (Japan's Stock Market)!

Japan's economy from the post-pandemic era has gone through incredible changes and reflects the complexities and diffculties facing financial markets and economies. This visualization was built using Python's Pandas and Matplotlib libraries.

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