The managed MLflow integration with Databricks on Google Cloud requires Databricks Runtime for Machine Learning 8.1 or above.
This section includes example notebooks using two of the most popular deep learning libraries, TensorFlow and PyTorch.
Because deep learning models are data- and computation-intensive, distributed training can be important. This section also includes information about and examples of distributed deep learning using Horovod and spark-tensorflow-distributor.
- Get started with TensorFlow Keras in Databricks
- Distributed training
- Deep Learning Pipelines