DP-3014 Implementing a Machine Learning solution with Azure Databricks
E-Learning
Description
Azure Databricks is a cloud-scale platform for data analytics and machine learning. Data scientists and machine learning engineers can use Azure Databricks to implement machine learning solutions at scale.
Azure Databricks is a cloud-scale platform for data analytics and machine learning. Data scientists and machine learning engineers can use Azure Databricks to implement machine learning solutions at scale.
| Lesson Id | Title | Description |
|---|---|---|
| 1 | Explore Azure Databricks |
Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts |
| 2 | Use Apache Spark in Azure Databricks |
Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data |
| 3 | Train a machine learning model in Azure Databricks |
Understand principles of machine learning Machine learning in Azure Databricks Prepare data for machine learning Train a machine learning model Evaluate a machine learning model |
| 4 | Use MLflow in Azure Databricks |
Capabilities of Mlflow Run experiments with Mlflow Register and serve models with Mlflow |
| 5 | Tune hyperparameters in Azure Databricks |
Optimize hyperparameters with Hyperopt Review Hyperopt trials Scale Hyperopt trials |
| 6 | Use AutoML in Azure Databricks |
What is AutoML? Use AutoML in the Azure Databricks user interface Use code to run an AutoML experiment |
| 7 | Train deep learning models in Azure Databricks |
Understand deep learning concepts Distribute PyTorch training with Horovod Train models with PyTorch |
Self-Paced
$33.49
This course includes: :
Full lifetime access