This project aims to develop a crop recommendation system using a Random Forest machine learning model. The system uses a dataset containing information about soil type i.e. PH value and weather factors like temperature, humidity and rainfall to recommend the most suitable crops for a given location.
A neural network-based crop recommendation system leveraging soil and environmental data. Achieved 98% accuracy through hyperparameter tuning and evaluation of two architectures with 2 and 5 hidden layers.
FARM FUTURO is a cutting-edge Machine Learning (ML) project designed to address the challenges faced by farmers in making informed crop decisions
This project aims to develop a crop recommendation system using a Random Forest machine learning model. The system uses a dataset containing information about soil type i.e. PH value and weather factors like temperature, humidity and rainfall to recommend the most suitable crops for a given location.
A machine learning system that makes crop recommendations based on soil and weather data.
A Intelligent Crop Recommendation Portal Using Machine Learning and Deep Learning
YIELTOR is a webpage used by farmers to know the information about which crop is grown at which time to give the best yield and profit from the crop
An application for Farmers to recommend them the best types of crops which can be cultivated on a certain piece of land using Soil Image.
Cultivating yield with an intelligent crop recommendation system
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
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.
Crop Recommendation
Smart Irrigation System
ML based Smart Crop Recommendation System with Disease Identification, utilizing CNNs. It aids farmers in selecting crops, managing diseases, and boosts productivity by integrating weather and geolocation APIs.
Some AIML Projects
Crop recommendation Web Application using Machine Learning along with fertilizer and cultivation season recommendation made with flask. The Prediction is performed using Random Forest Model
Crop Prediction Using TinyML and Arduino Nano BLE 33 Sense
Crop Recommendation is a web application that suggest/recommend the farmer to which crop to grown his/her field.
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