Wrap-up

Machine Learning End-to-End

Joshua Stapleton

Machine Learning Engineer

How far we've come

Built a full ML pipeline:

  • Problem Definition
  • Data Cleaning
  • Feature engineering and selection
  • Model Training and evaluation
  • Model deployment using TDD and CI/CD
  • Model monitoring
  • Feedback loop

Full ML lifecycle

Machine Learning End-to-End

What's next?

Large Question-mark

Machine Learning End-to-End

So much more to do!

  • ML lifecycle isn't a once-off solution.
    • It's iterative, organic.
    • Continue to improve!
Machine Learning End-to-End

Let's practice!

Machine Learning End-to-End

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