Covers: theory of MLOps
Estimated time needed to finish: 2 minutes
Questions this item addresses:
  • What is MLOps?
  • How can I use MLOps?
How to use this item?

This video talks about the components of MLOps, esp:

  • Model packaging
  • Containerization
  • Model training, serving, deployment
  • Scalability, monitoring, infrastructure as code
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Author(s) / creator(s) / reference(s)
Brendan McGivern
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Getting Started With Machine Learning Operation - MLOps

Total time needed: ~8 hours
This recipe aims to get you started and prepare you to operationalize your ML models
Potential Use Cases
machine learning model productionization
Who is This For ?
INTERMEDIATEData Scientists, Machine Learning Engineers
Click on each of the following annotated items to see details.
VIDEO 1. Introduction to MLOps
  • What is MLOps?
  • How can I use MLOps?
2 minutes
RECIPE 2. Preparing Trained Models for Production
81 minutes
RECIPE 3. Delivering your Models to End Users
2 hours
RECIPE 4. Preparing Your Infrastructure for Production
57 minutes
VIDEO 5. Creating an AWS account and GitHub account
  • How to set up AWS?
  • How to set up GitHub?
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VIDEO 6. Intro to Terraform
  • What is teraform used for?
12 minutes
VIDEO 7. Cortex Platform Demo
  • How can Cortex be used for model deployment?
14 minutes
RECIPE 8. What Is MLOps?
3 hours
VIDEO 9. Anaconda - Installation and Using Conda
  • How to install and use conda?
11 minutes
ARTICLE 10. Deploy Machine Learning Pipeline on AWS Fargate
  • How can we deploy models to AWS?
30 minutes
VIDEO 11. Kubernetes Tutorial for Beginners [FULL COURSE in 4 Hours] - YouTube
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Concepts Covered

Manuel Ángel Suarez Álvarez.
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