An end-to-end machine learning project to predict the sale price of bulldozers. This repository details a full data science workflow, including data preprocessing, model training with scikit-learn pipelines, hyperparameter tuning, and model evaluation.

High-performance UMAP C++ library with C# wrapper - featuring model persistence and transform capabilities based on umappp

End-to-end PySpark ML pipeline with ETL, feature engineering, regression modeling, and model persistence for airfoil noise prediction.

A Python project that predicts car models based on customer attributes like Gender and Color using a Decision Tree Classifier. Includes categorical encoding, model persistence, accuracy evaluation, and basic data analysis with pandas.

Predict airfoil self-noise using PySpark with an end-to-end machine learning pipeline on NASA dataset for aerodynamics and acoustics analysis.

🚗 Predict car models using decision tree classification based on user attributes like gender and color while analyzing automotive datasets effectively.