📊 Analyze and visualize superstore sales data using Python, SQL, and Power BI to uncover insights that drive strategic business decisions.

⚙️ Enhance machinery reliability with this AI-driven predictive maintenance system, predicting failures and estimating Remaining Useful Life using advanced models.

📊 Explore linear programming and mathematical optimization using Google OR-Tools to solve complex problems with practical Python models.

🌍 Implement climate prediction models to transform global data into localized forecasts for effective water resource management and impact assessment.

🚗 Predict used car prices accurately with machine learning models using various regression techniques and market data analysis for fair valuation.

A new library for all of the newest ai algorithms

A portfolio of data science and machine learning projects, featuring predictive modeling, EDA, and interactive Gradio web apps.

This project demonstrates a full MLOps pipeline for predicting flight prices using historical travel data. It integrates data preprocessing, machine learning modeling, REST API deployment, workflow orchestration, and CI/CD automation.

Pattern Recognition assignment

Machine learning (ML) is a subset of artificial intelligence (AI) that enables computers to learn from data, identify patterns, and make decisions without explicit programming.

A review of hands-on Data Science concepts done in 2025, when getting ready to start a job as a data scientist.

Library for Fast Segmented Regression

Market Indicators ingestion, normalization and ML training.

A Machine Learning Microservice for Knox

Production-ready ML pipeline for predicting fuel consumption (ton-kilometer) in heavy mining equipment. Features modular architecture, cyclic feature engineering, and automated pre-processing.

ML regression project to predict residential property prices in Bengaluru using Scikit-learn, Pandas & Python. Built with Linear Regression on the Bengaluru House Price dataset.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

Various machine learning models

In this project, I had performed exploratory analysis, visualization and prediction of used car prices and deployed the model with streamlit web app.