This is a recurring event: View all events in the series “Data Bites”
Speaker: Oleksandra Bovkun, Databricks
Target audience
DS and ML practitioners interested in using Machine Learning on Databricks
Prerequisites
- Beginning-level knowledge of the Databricks Lakehouse platform
- Intermediate-level knowledge of Python
- Intermediate-level knowledge of machine learning workflows.
Abstract
Databricks Machine Learning offers data scientists and other machine learning practitioners a platform for completing and managing the end-to-end machine learning lifecycle.
It streamlines the entire machine learning lifecycle, making it easier than ever to train and implement your own AI models.
The platform democratizes AI, providing tools that are as effective for seasoned AI engineers as they are for those just starting out in the field.
During this session, we’ll take a look at creating, training, deploying, and governing AI models with Databricks Machine Learning.
At this event, you will get the chance to:
- Learn how to scale exploratory data analysis and data science workflows with Databricks
- Learn best practices for training models and managing experiments, projects and models using MLflow
- Deploy machine learning models to production and monitor their performance
- Govern all your AI assets.
Attendance at City events is subject to our terms and conditions.