https://www.markdownguide.org/basic-syntax/

Croptimizer is a project developed by Laira L, Meghan L, Stella H, and Arjun R during the SMathhacks 2024 event. It is aimed at helping farmers optimize their crop selection based on various environmental factors using machine learning techniques.

Croptimizer leverages the scikit-learn machine learning library to build a model that predicts the feasibility of growing crops in an area based on factors such as temperature, humidity, pH levels, and rainfall. By analyzing historical crop data and environmental conditions, Croptimizer provides insights to farmers, enabling them to make informed decisions about crop selection for optimal yield.

To use Croptimizer, follow the steps below:

1. Provide your surroudning environemntal data using the sliders on the main home page. Include the annual average temperature, humidity, pH, rainfall, nitrogen, potassium (k), and phosphorous.
2. If you would like to use the Croptimizer at any location in the world, choose "Predict your Crops" option. However, note that this database is based off of data from India. Note that units chosen for potassium and phosphorous need to be consistent throughout the data. This data will output feedback regarding recommendations on crops suitable for your soil composition.
3. If you are located in Pakistan, choose "Pakistan Application." This option is specifically made for farmers in Pakistan and will ask to input your state. This data will output feedback regarding recommendations on crops suitable for your soil composition in your regions.

This project is licensed under the MIT License. See the LICENSE file for details.

We would like to thank the SMathhacks 2024 organizers for providing us with the opportunity to work on this project!