- Course
Building Deep Learning Models on Databricks
Learn to build, train, and deploy deep learning models on Databricks. This course will teach you to leverage distributed computing, MLflow experiment tracking, and the Databricks Model Registry to operationalize neural networks at scale.
Intermediate
- Course
Building Deep Learning Models on Databricks
Learn to build, train, and deploy deep learning models on Databricks. This course will teach you to leverage distributed computing, MLflow experiment tracking, and the Databricks Model Registry to operationalize neural networks at scale.
Intermediate
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This course is included in the libraries shown below:
- AI
What you'll learn
Scaling deep learning workflows is one of the biggest challenges facing AI engineers today.
In this course, Building Deep Learning Models on Databricks, you'll gain the ability to design, train, and deploy production-grade neural networks using Databricks' unified analytics platform.
First, you'll explore the Databricks environment and learn how to configure clusters for distributed deep learning with PyTorch.
Next, you'll discover how to track experiments systematically using MLflow, and how to optimize model performance at scale.
Finally, you'll learn how to register, version, and serve models through the Databricks Model Registry for real-world deployment.
When you're finished with this course, you'll have the skills and knowledge of distributed deep learning on Databricks needed to confidently move models from notebook to production.
Building Deep Learning Models on Databricks
Intermediate
Table of contents
Dr. Yasir Khan is a global tech consultant and 38Labs founder. He's passionate about digital transformation, data & AI, and regularly shares technology insights on Pluralsight.
