This GitHub repository features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices. You can also check them out in our Gallery.
We are looking for interesting colab notebooks(Jupyter notebooks) covering intermediate to advance level ML/DL techniques, best practices, a minimal implementation of research papers, benchmark on a dataset, etc.
The colab notebook should come with Weights and Biases integration. To get started with W&B:
- ❄️ Check out our examples repo.
- ⚡ Check out our official documentation.
- 🙌 (optional) If you want to create a report to document your experiment and observations check our reports video.
If you are working on an exciting ML/DL project, we would love to feature your work in this repo. The rules are simple:
- Create a new issue with a relevant title. Briefly describe the project you are working on in a meaningful manner. Provide links wherever necessary.
- We will review the issue and approve the idea if it meets the intermediate or advanced level mark.
- Fork this repo.
- Create a PR with a notebook. We have provided a template for the PR that will be auto-generated.
If we like your notebook, we will reach out to you for our Authors Program.
If you are passionate to showcase your machine learning research in a transparent and collaborative environment, you can even reach out to us using this typeform.