This app uses a Dataset with 2200 Datapoins for Training and for Generating predictions.
Model used: Gaussian Naive Bayes
Accuracy: 99.54%
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Just click on this [link]https://github.com/Satyanaryana-Merla/Crop-Recommendation-system
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Enjoy!
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Download the Github Package from this repo and Unzip it anywhere.
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Download and install Anaconda for Windows from this link or Jupyter for Windows from this link.
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Open Jupyter Notebook and navigate to the Crop-Recommendation folder.
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Launch a new Jupyter Terminal and type these commands
pip install streamlit
pip install pandas
pip install scikit-learn
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Now navigate to Crop-Recommendation folder using
cdcommand in the terminal. -
Type this command
streamlit run app.py
- Enjoy!
Many farmers are confused when making the choice before the sowing season. This app will help them with their choice and save them a lot of time and money.
It takes input about the Farmer's soil and tells them which Crop would be best for their soil type using ML prediction.
We have used a dataset of 2200 entries and trained an ML model on it for making the predictions. We have then used Streamlit library to create a user-friendly and simple UI for anyone to use. It uses Jupyter environment to run.
Finding the right dataset, Training the model for high accuracy, Hosting the model as a web-app.
High Accuracy of our ML model (99.54% during validation). Custom UI elements on Streamlit web-app.
Machine Learning, Using Streamlit for Hosting, Creating custom environment on Jupyter.