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Building deep learning models may take a lot of time. But not with AutoDL.
Automate your meta-work so that you can focus on building your models without the hassle of writing code.

• ✨ Use our interactive model builder and AI powered suggestion system to quickly whip out a working DL model. ✨

• ✨ Trained your model for multiple hours and found out that it's bugged? Not anymore. With AutoDL's AI ecosystem validate your model before you train it. ✨

• ✨ Host your model just as easily as you created it. ✨

• If an issue is not "assigned," you can assume that no one is working on it (may NOT be true). So to be sure, you can ask the following:

  • Can I take this up?
  • Also, mention a rough deadline until which you plan to fix the issue
  • (Optionally) Potential fixes DO NOT CREATE a pull request FIRST if someone else is working on it then your efforts might be wasted. Claiming doable and unclaimed issues should be the priority

• Conventional commits in the PR title are a must

• For frontend, while creating a pull request attach a screenshot of the change

• Last but not least, one pull request to fix a typo is fine, but 5 pull requests to remove a stray whitespace is not (reference).

The docs are the perfect place for you to start getting used to Auto-DL.

• Start with our getting started docs.

• The doc didn't help? Join our slack and ask your questions!

• You can directly jump to the user guide :)

The contributing guidelines hosts all the information about building Auto-DL from source, how to contribute code and documentation, who to contact about what, etc.

Setup Auto-DL:

• Bare-metal way
• Using Docker

• Improve the UI and UX.

• Show model training related stats on the frontend.

• Visualization and data preprocessing steps.

• Model Explainability.

Read the FAQ or send us a mail at [email protected]

For more details, visit our website

GNU General Public License v3.0