A weekly Python podcast hosted by Christopher Bailey with interviews, coding tips, and conversation with guests from the Python community. The show covers a wide range of topics including Python programming best practices, career tips, and related software development topics. Join us every Friday morning to hear what's new in the world of Python programming and become a more effective Pythonista.
Scaling Data Science and Machine Learning Infrastructure Like Netflix
Would you move your data science project from a laptop to the cloud? Would you also like to have snapshots of your project saved along the way so that you can go back in time or share the state of your project with another team member? This week on the show, we have Savin Goyal from Netflix. Savin is the technical lead for machine learning infrastructure at Netflix. He joins us to talk about Metaflow, an open-source tool to simplify building, managing, and scaling data science projects.
Metaflow addresses the needs of the numerous data scientists who work at Netflix. Machine learning is key strength for the streaming service. They tried several existing tools to scale their own internal infrastructure and after this experimentation developed Metaflow.
We talk about the history of the project and how someone could get started with the open-source version. Savin also contrasts the cost of infrastructure as compared to data scientists and the cost of their time.
Course Spotlight: Simplify Python GUI Development With PySimpleGUI
In this step-by-step course, you’ll learn how to create a cross-platform graphical user interface (GUI) using Python and PySimpleGUI. A graphical user interface is an application that has buttons, windows, and lots of other elements that the user can use to interact with your application.
Topics:
- 00:00:00 – Introduction
- 00:01:53 – What is Metaflow?
- 00:04:15 – Savin’s background in data science and infrastructure
- 00:06:06 – Democratization of infrastructure and iteration of tools
- 00:10:34 – What information is saved about the infrastructure requirements for a project?
- 00:17:17 – How are the requirements annotated?
- 00:18:39 – Sponsor: Digital Ocean’s App Platform
- 00:19:15 – How do project snapshots work?
- 00:29:33 – Cost of infrastructure vs data scientists
- 00:32:28 – Working with data at Netflix scale
- 00:37:55 – Video Course Spotlight
- 00:39:06 – Getting an organization to use new tools and then making open-source
- 00:49:51 – Documentation of Metaflow and getting started on solving infrastructure problems
- 00:53:57 – What made you interested in working on infrastructure tools?
- 00:55:13 – What is something you are excited about in the world of Python?
- 00:56:18 – What do you want to learn next?
- 00:58:14 – Thanks and goodbye
Show Links:
- Metaflow: A framework for real-life data science
- Metaflow: Tutorials
- More Data Science, Less Engineering with Netflix’s Metaflow By Savin Goyal - YouTube
- R: The R Project for Statistical Computing
- Tidyverse: R packages for data science
- Anything you can do, I can do (kinda). Tidyverse pipes in Pandas
- reticulate: R Interface to Python
- Apache Airflow: Programmatically author, schedule and monitor workflows
- Directed acyclic graph (DAG) - Wikipedia article
- Serializing Objects With the Python pickle Module - Real Python Course