A web-based mini project developed to predict fertilizers for crops based on different parameters (soil type, temperature, humidity, NPK values etc).
Python version, libraries and tools used / required - Python 3.11, Numpy v1.25, Scikit-Learn v1.2.1, Pandas, Matplotlib, Seaborn, Flask, HTML, CSS
Dataset (Fertilizer Prediction.csv) obtained from kaggle
To run the application, first run the prediction.py file to generate the pickle file which contains the trained model, then run app.py to run the application and click the generated link to launch the interface
Created by Atharva Ghongade, Abhijit Khole, Abhishek Chaudhari, Bhushan Raut and Piyush Kurwade (Pune Institute of Computer Technology)