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Lessons Learned From Hosting the ML Engineered Podcast (Charlie Interviewed on the ML Ops Community podcast)

Podcast |: Machine Learning Engineered
Publisher |: Charlie You
Media Type |: audio
Podknife tags |: Artificial Intelligence,; Business,; Careers,; Data Science,; Interview,; Machine Learning,; Technology
Categories Via RSS |: Business,; Careers,; Science,; Technology
Publication Date |: Feb 02, 2021
Episode Duration |: 01:03:58

Description
iTunes Summary

Learn more about the ML Ops Community: https://mlops.community/

Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: https://cyou.ai/newsletter

Follow Charlie on Twitter: https://twitter.com/CharlieYouAI

Subscribe to ML Engineered: https://mlengineered.com/listen

Comments? Questions? Submit them here: http://bit.ly/mle-survey

Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/

Timestamps:

02:45 Intro

04:10 How I got into data science and machine learning

08:25 My experience working as an ML engineer and starting the podcast

12:15 Project management methods for machine learning

20:50 ML job roles are trending towards more specialization

26:15 ML tools enable collaboration between roles and encode best practices

34:00 Data privacy, security, and provenance as first class considerations

39:30 The future of managed ML platforms and cloud providers

49:05 What I've learned about building a career in ML engineering

54:10 Dealing with information overload

Links:

Josh Tobin: Research at OpenAI, Full Stack Deep Learning, ML in Production

The Third Wave Data Scientist

Practical ML Ops // Noah Gift // MLOps Coffee Sessions

Building a Post-Scarcity Future using Machine Learning with Pavle Jeremic (Aether Bio)

SRE for ML Infra // Todd Underwood // MLOps Coffee Sessions

Luigi Patruno on the ML Ops Community podcast

Luigi Patruno: ML in Production, Adding Business Value with Data Science, "Code 2.0"

I was recently interviewed by Demetrios and Vishnu from the ML Ops Community podcast. We discuss my experience working as an ML engineer and starting the podcast, lessons learned from talking to experts, and trends we've noticed in the industry.