Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

AutoML classification docs #22

Closed
wants to merge 1 commit into from
Closed

AutoML classification docs #22

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 3 additions & 0 deletions classification/README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -20,9 +20,12 @@ you will learn how to use MLflow Recipes to
- Splits the dataset into training/validation/test.
- Create an identity transformer and transform the dataset.
- Train a linear model (classifier) to tell if a bottle of wine is red.
- Train via AutoML
- Evaluate the trained model, and improve it by iterating through the `transform` and `train` steps.
- Register the model for production inference.

We support training via AutoML by simply specifying `using: automl/flaml` in the `train` step.

All of these can be done with Jupyter notebook or on the Databricks environment.
Finally, challenge yourself to build a better model. Try the following:
- Find a better data source with more training data and more raw feature columns.
Expand Down