Added my solutions for the gsoc'24 toy test for ML/DL by Nasa, solving Issue #243
Description and Analysis:
This PR demonstrates how I systematically explored galaxy measurement interpolation methods, including linear and polynomial interpolation, PyTorch-based neural networks (ML/DL), and support vector regression model. Through meticulous evaluation and visual confirmations, I showcased their efficacy and accuracy in predicting measurements at desired wavelengths.
Linear Interpolation Results
Polynomial Interpolation Results
DL-ML based Interpolation Results
Support Vector Machine based Interpolation Results
Added my solutions for the gsoc'24 toy test for ML/DL by Nasa, solving Issue #243
Description and Analysis: This PR demonstrates how I systematically explored galaxy measurement interpolation methods, including linear and polynomial interpolation, PyTorch-based neural networks (ML/DL), and support vector regression model. Through meticulous evaluation and visual confirmations, I showcased their efficacy and accuracy in predicting measurements at desired wavelengths.
Linear Interpolation Results
Polynomial Interpolation Results
DL-ML based Interpolation Results
Support Vector Machine based Interpolation Results