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

Episode 19

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

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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


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"

About the Podcast

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Machine Learning Engineered
Helping you bring ML out of the lab and into products that people love.

About your host

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Charlie You

Charlie currently works as a Machine Learning Engineer at Workday. He graduated from RPI with a B.S. in Computer Science and taught himself ML through online courses and projects. In his free time, Charlie enjoys investing and trading, playing poker, and training Brazilian Jiu-Jitsu.