Kunal Chindarkar

This project is an SMS/Email Spam Classifier built using Machine Learning and deployed with Streamlit. It predicts whether a message is Spam or Not Spam (Ham) by analyzing the text content.

An end-to-end Machine Learning project that predicts heart disease risk using patient medical data. Includes data preprocessing, exploratory data analysis (EDA), feature scaling, multiple classification models, model evaluation, feature importance analysis, and prediction using Python and Scikit-learn

Developed an interactive Power BI dashboard to analyze Uber ride operations, revenue performance, vehicle-wise trends, cancellations, and customer ratings. Built multiple analytical views including Overall Performance, Vehicle Type Analysis, Revenue Insights, Cancellation Analysis, and Ratings Dashboard.

Mini project to predict churn

End-to-end data analysis pipeline exploring academic performance trends across multi-subject datasets. Includes data cleaning, EDA, visualizations (bar charts, scatter plots, correlation matrices), and descriptive statistics to derive insights for educational stakeholders.

Collaborative filtering-based recommendation system that suggests items based on user behavior and similarity patterns. Includes data preprocessing, EDA, user item matrix creation, cosine similarity for personalized recommendations, and Flask deployment as a REST API.

PROJECT MADE WITH PYTHON

PROJECT MADE WITH PYTHON

Python & data science practice — preprocessing, EDA, ML concepts applied on real/sample datasets

SQL practice — one problem (joins, window functions, subqueries, CTEs) with solutions and approach notes.