KnowCrop

Inspiration

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.

What it does

It takes input about the Farmer's soil and tells them which Crop would be best for their soil type using ML prediction.

How we built it

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.

Challenges we ran into

Finding the right dataset, Training the model for high accuracy, Hosting the model as a web-app.

Accomplishments that we're proud of

High Accuracy of our ML model (99.54% during validation). Custom UI elements on Streamlit web-app.

What we learned

Machine Learning, Using Streamlit for Hosting, Creating custom environment on Jupyter.

What's next for KnowCrop

Finding a better dataset for more accurate predictions. Proper web hosting solution for anyone to use.

Built With

• jupyter
• python
• streamlit