Train models

This section covers how to train machine learning and deep learning models on Databricks, and includes examples using many popular libraries. You can also use Databricks AutoML, which automatically prepares a dataset for model training, performs a set of trials using open-source libraries such as scikit-learn and XGBoost, and creates a Python notebook with the source code for each trial run so you can review, reproduce, and modify the code.

• Machine learning
  • scikit-learn
  • MLlib
  • XGBoost
• Deep learning
  • Get started with TensorFlow Keras in Databricks
  • TensorFlow
  • PyTorch
  • Distributed training
  • Deep Learning Pipelines
• Hyperparameter tuning
  • Automated MLflow tracking
  • Hyperparameter tuning with Hyperopt