This APOGEE, IEEE BITS Pilani, brings to you, ML Codeathon. This time we have something for everyone - a challenge for the beginners as well as the experts. Show your skills at Deep Learning and Artificial Intelligence!
- All information can be obtained from the D2C ML Codeathon Page.
- The GitHub Repo contains the Jupyter Notebook with the instructions and the problem statement.
- The GitHub Repo also contains the dataset and sample code for the participants’ reference.
- Participants can open the Jupyter Notebook in Google Colab using ‘Open in Colab’ button on top left of the Jupyter Notebook. Then create a copy of the Notebook in your Drive to begin working.
- Alternatively, the participants can download the Jupyter Notebook and work locally.
- The code for loading the dataset is provided in the Jupyter Notebook such that the participants can run the Jupyter Notebook on Colab or Locally and the dataset would be downloaded from GitHub and loaded.
- All instructions provided in the Notebook are to strictly followed for the submission to be considered.
- Make sure to submit the exact files asked.
- Make sure that all the preprocessing done on the data is done in the Jupyter Notebook you submit because we would be running your code on our original dataset.
Files to be Submitted are given below. Elaborate instructions are provided in the Jupyter Notebook.
- Python notebook (.ipynb) file with outputs
- Saved models (.pt) file
- submission.json file