This repository demonstrates multiscale modeling of copper heat pipes using machine learning, integrating grain-scale data with FEA via a UMAT. It highlights grain size’s impact on stress, strain, and heat transfer for optimized material design.

Learning python day 3

This repository contains code for Machine Learning (beginner level) using Python.

Building Polynomial Regression with Typescript

Can find example code to know how different ml algorithm like SVR,RF,XGBoost etc are applies in real time

This repository contains various regression models built using Python, including Linear Regression, Polynomial Regression, and Multiple Linear Regression. Each model is trained and evaluated on real-world datasets with clear visualizations using Matplotlib and Seaborn.

Polynomial regression Using numpy's polyfit and matplotlib