Skip to content

Latest commit

 

History

3 Commits

Folders and files

NameName
Last commit message
Last commit date
 
 
 
 
 
 

Repository files navigation

ML_Physics_Engineered

Selected for final offline round (top 10) among 2k+ registration and ~375 valid submissions . Couldn't attend the final round due to academic commitments .

Developed an ML Algorithm for the given datasets using physics guided feature engineering (catalytic reaction domain) together with ensemble learning achieving a RMSE of 10.94 , MAE of 2.76 and R2 score of 0.91.

Problem statement is publicly available and is attached in this repo taken from Fugacity ML Hackathon (IIT KGP 26) kaggle for reference . Please refer to the notebook for the end to end solution with clear decisions and explanations

About

Developed an ML Algorithm for the given datasets using physics guided feature engineering (catalytic reaction domain) together with ensemble learning

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages