ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.

crop-prediction 开源项目推荐(86 个)
crop-prediction 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 86 个仓库An all purpose flutter app for farmers made under Food and Agriculture theme in Accelathon hackathon
AI智能农业助手采用机器学习和CNN等先进技术,通过用户友好的网页应用为农民提供作物推荐、病害识别、天气预报、肥料推荐和作物管理指导。
Developed a machine learning-based crop prediction model to assist farmers in making informed decisions about crop selection, planting, and harvesting.Integrated weather and geolocation APIs along with a web page for simplified user experience.
The Crop Management System is a machine learning-based project designed to provide predictions and recommendations for farmers.
The model focuses on predicting the crop yield in advance by analyzing factors like district (assuming same weather and soil parameters in a particular district), state, season, crop type using various supervised machine learning techniques. This helps the farmers to know the crop yield in advance to plan and choose a crop that would give a bett…
SmartCrop: Intelligent Crop Recommendation
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
A mobile application involving machine learning to recommend crop variety and also predict crop yield.
An Intelligent Crop Recommendation system using Machine Learning that predicts crop suitability by factoring all relevant data such as temperature, rainfall, location, and soil condition. This system is primarily concerned with performing AgroConsultant's principal role, which is to provide crop recommendations to farmers.
Predicting Crop Yield.
Revolutionize your farming with Farmwiser, the ultimate TinyML based Smart Agriculture solution!
Android application which includes features like best crop prediction using ML model, live weather, live news Feed and much more. 😀
The AI-driven Crop Prediction System that applies Machine Learning and AI to analyze weather, soil, and crop data to predict crop health and yield. This system provides farmers with precise predictions, empowering them to make data-driven decisions and enhance their farming practices.
"Excited to share my latest project on LinkedIn: a crop yield prediction ML model deployed with Streamlit! 🌱 Leveraging the power of Stochastic Gradient Descent regression(SGD) algorithm, this tech-driven solution boasts an impressive 94% accuracy on both training and testing data.
This Github Repository Contains a machine learning powered crop price prediction application with a firebase connected login and signup
Prediction of suitable crop using soil and weather conditions.
Build@ARSD - Tech for Good
An AI-powered Smart Agriculture System using Flask, Machine Learning, MySQL, ESP32, and an Interactive Dashboard for crop recommendation, yield prediction, irrigation planning, and farm analytics.
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/crop-prediction。
- 该话题在 GitHub 上共有 86 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 501 Star,覆盖 7 种主要语言,数据更新于 2026-11-12。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。