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Ask the Expert: Understand the ML Process and Embed Models into Apps
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Machine Learning is becoming an important workload, and developers are increasingly being tasked with moving the models to production. We’ll walk you through the process of building machine learning models and show you how Azure ML enables tools like VS Code, to build ML models. Join us to discuss how you can augment your data science teams to operationalize these machine learning models within your apps and incorporate the right DevOps practices for machine learning, often referred to as MLOps.
Jump to:
00:00 - Introduction
01:23 - Understand the ML Process and Embed Models into Apps
03:52 - Machine Learning Overview
05:46 - Geometric Brownian motion (GBM)
11:33 - PyTorch Lightning
14:56 - Building a model with PyTorch Lightning
19:02 - Predicting your model
21:25 - MLOps
23:38 - How do you integrate this code in DevOps or Kubernetes?
25:22 - How do you get the model into your app?
28:17 - How can I learn more? Is there a community I can be a part of?
28:57 - Closing Notes
Jump to:
00:00 - Introduction
01:23 - Understand the ML Process and Embed Models into Apps
03:52 - Machine Learning Overview
05:46 - Geometric Brownian motion (GBM)
11:33 - PyTorch Lightning
14:56 - Building a model with PyTorch Lightning
19:02 - Predicting your model
21:25 - MLOps
23:38 - How do you integrate this code in DevOps or Kubernetes?
25:22 - How do you get the model into your app?
28:17 - How can I learn more? Is there a community I can be a part of?
28:57 - Closing Notes
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