Cursusbeschrijving

Azure Databricks is een platform op cloud-schaal voor gegevensanalyse en machine learning. Data scientists en machine learning engineers kunnen Azure Databricks gebruiken om grootschalige machine learning-oplossingen te implementeren.

Onderwerpen

  • Explore Azure Databricks
  • Provision an Azure Databricks workspace.
  • Identify core workloads and personas for Azure Databricks.
  • Describe key concepts of an Azure Databricks solution.
  • ### Use Apache Spark in Azure Databricks
  • Describe key elements of the Apache Spark architecture.
  • Create and configure a Spark cluster.
  • Describe use cases for Spark.
  • Use Spark to process and analyze data stored in files.
  • Use Spark to visualize data.
  • ### Train a machine learning model in Azure Databricks
  • Prepare data for machine learning
  • Train a machine learning model
  • Evaluate a machine learning model
  • ### Use MLflow in Azure Databricks
  • Use MLflow to log parameters, metrics, and other details from experiment runs.
  • Use MLflow to manage and deploy trained models.
  • ### Tune hyperparameters in Azure Databricks
  • Use the Hyperopt library to optimize hyperparameters.
  • Distribute hyperparameter tuning across multiple worker nodes.
  • ### Use AutoML in Azure Databricks
  • Use the AutoML user interface in Azure Databricks
  • Use the AutoML API in Azure Databricks
  • ### Train deep learning models in Azure Databricks
  • Train a deep learning model in Azure Databricks
  • Distribute deep learning training by using the Horovod library
  • Materiaal

    Digitaal Microsoft cursusmateriaal

    Voorkennis

    Ervaring met het gebruik van Python om gegevens te verkennen en machine learning-modellen te trainen met gangbare open source frameworks, zoals Scikit-Learn, PyTorch en TensorFlow. Overweeg om de leerweg 'Machine learningmodellen maken' te voltooien voordat je aan deze begint