Note
Access to this page requires authorization. You can try signing in or changing directories.
Access to this page requires authorization. You can try changing directories.
Try one of these tutorials to get started. You can import these notebooks to your Databricks workspace.
| Tutorial | Description |
|---|---|
| Classic ML | End-to-end example of training a classic ML model in Databricks. |
| scikit-learn | Use one of the most popular Python libraries for machine learning to train machine learning models. |
| MLlib | Examples of how to use the Apache Spark machine learning library. |
| Deep learning using PyTorch | End-to-end example of training a deep learning model in Databricks using PyTorch. |
| TensorFlow | TensorFlow is an open-source framework that supports deep-learning and numerical computations on CPUs, GPUs, and clusters of GPUs. |
| Trace a GenAI app | Trace an app's execution flow with visibility into every step. |
| Evaluate a GenAI app | Use MLflow 3 to create, trace, and evaluate a GenAI app. |
| Human feedback quickstart | Collect end-user feedback and use that feedback to evaluate your GenAI app's quality. |