This section showcases step-by-step case studies of how to combine the different features of Flyte to achieve everything from data processing, feature engineering, model training, to batch predictions. Code for all of the examples in the user guide can be found in the flytesnacks repo.
Flytesnacks comes with a highly customized environment to make running, documenting and contributing samples easy. If this is your first time running these examples, follow the setup guide to get started.
Train machine learning models from using your framework of choice.
Engineer the data features to improve your model accuracy.
Perform computational biology with Flyte.
The open-source repository of machine learning projects using Flyte.