Technical Portfolio
Selected data science and machine learning projects demonstrating end-to-end execution from problem definition to production deployment.
Interactive Demonstrations
Live demos and interactive showcases of my work:
A/B Testing Dashboard
Interactive A/B testing analysis and visualization tool built with modern web technologies.
View Demo →E-commerce Store
Personal e-commerce platform with analytics integration and modern UI/UX.
View Demo →Data Visualization
Interactive dashboards using Tableau, Excel, and Looker for data exploration and reporting.
View Demo →AI-Powered Products
Products built with Lovable, Cursor, and AI agents demonstrating modern development workflows.
View Demo →ML / Data Analytics Projects
Yelp Data Analysis
View Code →Tech Stack: Python, Pandas, NLP, TextBlob, NLTK, Folium, Seaborn
End-to-end NLP pipeline using TextBlob and NLTK. Performed EDA on 1M+ reviews.
Cash Flow Forecasting
View Code →Tech Stack: Python, LSTM, Prophet, ARIMA, Time Series Analysis
LSTM & ARIMA Time-series forecasting. Reduced execution time by 4 min/epoch.
Cookie Cats A/B Test Analysis
View Code →Tech Stack: Python, Pandas, Scipy, Statsmodels, Bootstrap, Logistic Regression
Advanced A/B test analysis with heterogeneous treatment effects, bootstrap confidence intervals, and policy simulation.
A/B Testing & Product Optimization
View Code →Tech Stack: Python, Logistic Regression, Statistical Testing
Designed and executed A/B tests with logistic regression models. Achieved 12 basis point increase in product usage rate.
News Recommendation System
View Code →Tech Stack: Python, LightGBM, DIN, Collaborative Filtering, Deep Learning
Personalized recommendation system using LightGBM, DIN, and collaborative filtering. Achieved 20% CTR increase.
E-commerce Pricing Optimization
View Code →Tech Stack: Python, XGBoost, Machine Learning
Dynamic ML pricing engine using XGBoost to optimize product pricing based on demand, competition, and market conditions.
Customer Segmentation (RFM)
View Code →Tech Stack: Python, K-Means Clustering, Customer Analytics
Full customer lifecycle analysis using Recency, Frequency, and Monetary value segmentation with K-Means clustering.