Description
Speaker:: Richard Pelgrim
Track: PyData: PyData & Scientific Libraries Stack A Pythonic introduction to methods for scaling your data science and machine learning work to larger datasets and larger models with Dask, all while staying within the comfort of the tools and APIs you know and love from the PyData stack (such as numpy, pandas, and scikit-learn).
We'll discuss: - How to reason about when you need to scale your data and machine learning work and when not to; - How to leverage distribute computation on your local workstation (such as your laptop) to analyze larger datasets and build larger, more complex models; - How to harness the power of clusters to support larger-than-memory computation, all from the comfort of your own laptop.
Recorded at the PyConDE & PyData Berlin 2022 conference, April 11-13 2022. https://2022.pycon.de More details at the conference page: https://2022.pycon.de/program/RTPEWV Twitter: https://twitter.com/pydataberlin Twitter: https://twitter.com/pyconde