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Deploying Machine Learning Models with Flask and Docker

Agenda

What happens after we train a model in a Jupyter notebook? It’s time to deploy it!
In this talk, we’ll learn about putting ML models into production and deploying it as a web service. We’ll cover:
  • Saving and loading models with pickle
  • Serving the model with Flask
  • Creating and managing virtual environments with Pipenv
  • Packaging the service in Docker
  • Deploying the model to the cloud with AWS Beanstalk
By the end of this session, you’ll be able to deploy any Scikit-Learn model to production.
Alexey Grigorev
Alexey Grigorev

Principal Data Scientist at OLX

Alexey lives in Berlin with his wife and son. He works as a principal data scientist at OLX and he runs DataTalks.Club — a community for data enthusiasts. Alexey wrote a few books about machine learning. One of them is Machine Learning Bookcamp — a book for software engineers who want to get into machine learning.

Resources