MLOps Platforms From Zero - Databricks, MLFlow-MLRun-SKLearn

MLOps Platforms From Zero - Databricks, MLFlow-MLRun-SKLearn

Pragmatic AI Labs via YouTube Direct link

Setting up Inference endpoint with the Databricks platform

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12 of 17

Setting up Inference endpoint with the Databricks platform

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Classroom Contents

MLOps Platforms From Zero - Databricks, MLFlow-MLRun-SKLearn

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  1. 1 Intro
  2. 2 Starting an MLOps project
  3. 3 Setup CI/CD
  4. 4 Invoke ML Library Code
  5. 5 End to End MLOps with Databricks to AWS Containers Diagram
  6. 6 Spinning up Databricks Cluster
  7. 7 Doing Pandas to Spark
  8. 8 Creating Fake News Classifier using Kaggle and AutoML
  9. 9 Creating Databricks AutoML Experiment
  10. 10 Viewing Databricks AutoML Experiment notebook
  11. 11 Registering models with Databricks
  12. 12 Setting up Inference endpoint with the Databricks platform
  13. 13 Using Github CodeSpaces to serve out downloaded Databricks model with MLFlow
  14. 14 Using FastAPI to serve Swagger documentation of MLFlow model
  15. 15 Feature Store Capabilities of Iguazio
  16. 16 Using AWS Cloud9 to develop containerized ML Models
  17. 17 Using AWS App Runner to serve out containerized model

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