/crop-analysis-and-prediction

Submission for the project component of the Data Visualisation (CSE3020) course.

Primary LanguageJupyter NotebookMIT LicenseMIT

Analysis of Total Geographical Land Use and Prediction of Crops using Various ML Models

Submission for the project component of the Data Visualisation (CSE3020) course taken in Winter 2022-23 semester under Prof. Pattabiraman V.

Running the project

  1. The main file is the Jupyter Notebook crop-analysis-and-prediction.ipynb.
  2. Install all Python modules needed by running python -m pip install -r requirements.txt in the same folder.
  3. Connect the ipynb file to a kernel (needed for running Jupyter notebooks). You can do this in VSCode by clicking the "Select Kernel" in the top right. It will install the necessary modules
  4. Run the entire file.

Team members:

  1. 20BCE1043 - Vishal N
  2. 20BCE1317 - Jyothssena GS
  3. 20BCE1360 - Prathiba N