Crop yield predictor
Personal Project
Summary
Developed an end-to-end Machine Learning pipeline that predicts agricultural output by synthesising environmental and chemical data. I curated a comparative analysis between the classical Scikit-Learn regressors and a custom PyTorch Neural Network on the data. And deployed the best of the two as an interactive Streamlit application.