Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

Create Interactive Dashboards with Streamlit and Python Coursera

An app that finds and compares statistically similar college football teams

Interactive Streamlit web app for analyzing NYC Airbnb listings with comprehensive EDA, pricing insights, geographic visualizations, and market trends analysis

Developed a Streamlit application for analyzing transactions and user data from the Pulse dataset. Explored data insights on states, years, quarters, districts, transaction types, and brands through EDA. Visualized trends and patterns using plots and charts to optimize decision-making in the Fintech industry.

DataMiner is an interactive web application for data mining and machine learning. It helps users upload, clean, transform, and analyze datasets while building predictive models — all through a simple and powerful Streamlit interface.

Interactive retail sales analytics dashboard with ML-powered forecasting, advanced data visualization, and customizable features. Supports custom CSV uploads and includes a sample dataset for immediate exploration

A Streamlit app that uses OpenAI's LLM for natural language data analysis. Upload CSV files, ask questions in plain English, and get instant insights. Powered by PandasAI, it's designed for quick, code-free exploration of structured data.

This project analyzes sales, profits, quantity and customer trends using SQL, Tableau providing insights on top-selling products, regional performance, customer segmentation, and order patterns to optimize business strategies.

Interactive sales dashboard built with Dash and Plotly for data exploration and visualization.