Recipe
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What Is MLOps?

Collaborators
Reviewers
Total time needed: ~3 hours
Learning Objectives
For me, a successful ML app is not only about the accuracy of the Model, but also the infrastructure around the model to make the model a scalable, stable application. This is where MLOps becomes important, to apply DevOps best practices into ML project.
Potential Use Cases
For the ones that are interested in MLOps or want to make your ML product more robust.
Target Audience
BEGINNERPeople interested in MLOps
Go through the following annotated items in order:
ARTICLE 1. What Is MLOps?
  • What is MLOps?
20 minutes
ARTICLE 2. MLOps: Continuous delivery and automation pipelines in machine learning
  • How to implement and automate CI, CD, CT for ML systems?
  • What are the differences between DevOps and MLOps?
  • What are the data science steps for ML?
  • What are the 3 maturity level of MLOps?
40 minutes
REPO 3. MLOps on Azure
  • How does Azure ML help with MLOps?
  • What are MLOps Best Practices?
  • What are MLOps Solutions using Azure?
  • What are the key challenges Azure with to solve with MLOps?
60 minutes
ARTICLE 4. Machine Learning Operations
  • Motivation for MLOps?
  • Designing ML-powered Software?
  • End-to-End ML Workflow Lifecycle?
  • Three Levels of ML-based Software?
  • MLOps Principles?
  • State of MLOps (Tools & Frameworks)?
30 minutes

Concepts Covered

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"Hands-on and practical exposure to deep learning while working with experts from industry and brilliant members is something that I was missing before finding this platform."

Werner C.

Data Scientist

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"Best Environment to discuss theory and implementation of the latest in machine learning and to continuously learn."

Susan S.

Data Scientist

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"Unlike other workshops, this experience included designing more than just machine-learning models. Full end-to-end AI solutions including MLOps was a necessary part of the Capstone. It was incredible to be able to conceptualize, design and build an AI product which resulted in attracting real investors."

Edward J.

Product Manager

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"I had a hard time keeping up with the latest in machine learning, let alone understanding and applying those concepts, until I found this community."

Emily W.

MSc Student

testimonial icon
"Hands-on and practical exposure to deep learning while working with experts from industry and brilliant members is something that I was missing before finding this platform."

Werner C.

Data Scientist

testimonial icon
"Best Environment to discuss theory and implementation of the latest in machine learning and to continuously learn."

Susan S.

Data Scientist

testimonial icon
"Unlike other workshops, this experience included designing more than just machine-learning models. Full end-to-end AI solutions including MLOps was a necessary part of the Capstone. It was incredible to be able to conceptualize, design and build an AI product which resulted in attracting real investors."

Edward J.

Product Manager

testimonial icon
"I had a hard time keeping up with the latest in machine learning, let alone understanding and applying those concepts, until I found this community."

Emily W.

MSc Student

testimonial icon
"Hands-on and practical exposure to deep learning while working with experts from industry and brilliant members is something that I was missing before finding this platform."

Werner C.

Data Scientist

testimonial icon
"Best Environment to discuss theory and implementation of the latest in machine learning and to continuously learn."

Susan S.

Data Scientist