AgML aspires to identify key research gaps and opportunities at the intersection of agricultural modelling and machine learning research and support enhanced collaboration and engagement between experts in these disciplines.
Machine Learning based Crop Yield Prediction
🌾 A Reproducible Pipeline for Processing the Global Dataset of Historical Yields (1981–2016) by Iizumi et al.
Crop yield prediction using ML on real-world weather, pesticide, and agricultural data.
Flask web app that predicts crop yield using CatBoost, XGBoost, and LSTM models.
Plan Disease Prediction Using Machine Learning Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials
Sustainable Crop Yield Prediction using Machine Learning
Description: 🌱 Smart Farm Yield Prediction Dashboard using PySpark, Streamlit, and Machine Learning for crop yield forecasting and interactive visual insights.
Published in IJITRA - Accessible Crop Yield Prediction Using Decision Trees: A Farmer-Oriented Web-Based AI Application
Using Docker and Keras to generate competition-worthy Crop Yield Prediction Models | ISTA429 Midterm project for Team X for MCLAS2021
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