Publication

Case Study: NY Real Estate Racial Equity Analysis via Applied Machine Learning This study analyzes tract-level real estate ownership patterns in New York State (NYS) and New York City (NYC) to uncover racial disparities.

Mr. & Mrs. Smith: Multi-Agent Mission System

Built a multi-agent, agentic AI system where two autonomous agents collaborate, critique, and refine mission plans. Designed role-based agents with distinct goals, implemented agent-to-agent feedback loops, and delivered an interactive web UI.

Chat with multiple PDF Documents with LangChain and Google Gemini Pro.

Developed an application leveraging Google's Gemini Pro model and Langchain library to implement a Language Model (LLM). This application allows users to input multiple PDF documents, which are processed using FAISS vector embeddings for analysis and retrieval. The FAISS vector embeddings facilitate

Movie Recommendation System

A Content-Based Movie Recommender System using Cosine Similarity which suggests movies by comparing features like overview, genre, keywords, cast, and crew. It calculates similarity scores between movies, recommending those with the highest relevance based on user preferences.

T20 World Cup Cricket Score Predictor

An XGBoost-based Cricket Score Predictor uses machine learning to forecast team scores in cricket matches. It leverages match-related features like overs played, wickets lost, and run rates to train an XGBoost regression model, providing accurate score predictions based on historical match data.

Sentimental Analysis of Twitter Data

Natural Language Processing(NLP) Problem where Sentiment Analysis is done for Classifying the positive tweets and negative tweets by machine learning models using classification, text mining, text analysis, data analysis and data visualization.

Credit Card Fraud Detection

Artificial Neural Network Model that predicts fraudulent credit card transactions based on various features by learning patterns and relationships within the data.

Heart Disease Prediction

Heart disease prediction using the Random Forest algorithm involves creating a model that can accurately classify whether a person is likely to have heart disease based on a set of input features.

NYC Taxi Trip Analysis

Analyzing NYC yellow taxi activities, such as which areas are more popular, at what time or day it is the busiest, and which area is more generous in terms of tipping.

Tableau Dashboards

Tableau Dashboards for visualizing insights on different datasets.