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.

We are looking for passionate people willing to cultivate and inspire the next generation of leaders in tech, business, and data science. If you are one of them get in touch with us!

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