Alyona Galyeva - We build a ML pipeline after we deploy
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/...
Please see our speaker release agreement for details: https://ep2021.europython.eu/events/s...
