Machine Learning Operations
This course will guide participants through an exploration of machine learning operations on Databricks. This will begin with an introduction to modern machine learning operations as a combination of DevOps, DataOps, and ModelOps, including an overview of each component. Next, the course will cover the Databricks-recommended architectures and solutions for machine learning operations. This will focus on capabilities like MLOps Stacks, MLflow, Model Serving, Unity Catalog, and Lakehouse Monitoring. Finally, the final section of the course will be a practical walkthrough of a simple machine learning operations project using these capabilities, including: an initial development phase, a staging phase, and a production stage. By the end of this course, learners will be familiar with the basic end-to-end machine learning operations workflow on Databricks.
Languages Available: English | 日本語 | Português BR
At a minimum, you should be familiar with the following before attempting to take this content:
Basic knowledge of traditional machine learning concepts
Beginner experience with traditional machine learning development on Databricks
Intermediate knowledge of Python for machine learning projects
Upcoming Public Classes
Date | Time | Language | Price |
---|---|---|---|
Sep 06 | 01 PM - 05 PM (America/New_York) | English | $750.00 |
Sep 24 | 08 AM - 12 PM (Australia/Sydney) | English | $750.00 |
Nov 26 | 08 AM - 12 PM (America/Los_Angeles) | English | $750.00 |
Nov 27 | 01 PM - 05 PM (Europe/London) | English | $750.00 |
Nov 29 | 09 AM - 01 PM (Asia/Kolkata) | English | $750.00 |
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