Training schedule
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Contact Gert-Jan Steltenpool, if you want to know more about custom data & AI training for your teams. He’ll be happy to help you!
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Production Ready Machine Learning
Learn the best practice to bring your machine learning models into production with this practical training about how software engineers manage their code, how more advanced Python features can make your life easier, and how to go from notebooks to packages in this 2-day course.
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What you'll learn
You will learn:
During this training, you will go in-depth with the tools and technique to bring your Machine Learning code to production more easily. After this training, you are knowledgeable about the following topics.
- How documentation, testing, and modularity help creating more robust code
- How type hinting can greatly reduce the number of bugs in your code
- How continuos delivery for Machine Learning works and how it improves your workflow
- Practical advice on how to go from notebook to package
- How Python’s Object Oriented features can help you structure your scikit-learn code
The schedule
- Continuos delivery for Machine Learning
- Monitoring and testing Machine Learning
- Solution Design for Machine Learning applications
- Packaging Machine Learning models and Python code
- Linting and code formatting as part of the CI/CD pipelines
- Testing with pytest
- Creating a command line interface for your packages
- Implementing a REST API on top of your models