Description
We build a ML pipeline after we deploy [EuroPython 2021 - Talk - 2021-07-29 - Parrot [Data Science]] [Online]
By Alyona Galyeva
This talk covers the importance of building end-to-end machine learning pipelines from day one.
What you will learn: - why we need a machine learning pipeline and when to use it; - ML pipeline building blocks covering training and inference; - engineering around failures and engineering for performance; - ML pipelines debugging and monitoring; - open-source Python libraries to save your time.
For whom: - data scientists, data analysts, data engineers, machine learning engineers, data product owners, Python developers, working or willing to work with machine learning.
Prerequisites: to get the most out of this talk, Data Science, ML, and Python experience is recommended
License: This video is licensed under the CC BY-NC-SA 4.0 license: https://creativecommons.org/licenses/by-nc-sa/4.0/ Please see our speaker release agreement for details: https://ep2021.europython.eu/events/speaker-release-agreement/