Explore a 46-minute podcast episode featuring Stephen Batifol discussing the process of building an ML platform, fostering community, and promoting advocacy. Gain insights into Wolt's approach to onboarding data scientists, creating a thriving internal user community, and prioritizing developer relations. Learn about the importance of comprehensive documentation, getting-started guides, and tutorials in simplifying data scientists' workflows. Discover Stephen's journey from Android developer to Machine Learning Engineer and his perspective on applying software engineering best practices to machine learning. Delve into topics such as DevRel, data platforms, open-source deployments, and the integration of language models in business. Gain valuable knowledge about gathering user feedback, conducting surveys, and evangelizing ML platforms. Explore the tech hub culture in Berlin, Kubernetes lifestyle, and interactions with Site Reliability Engineers (SREs) in this informative discussion on MLOps and ML platform development.
Building an ML Platform: Insights, Community, and Advocacy - MLOps Coffee Sessions
Overview
Syllabus
[] Stephen's preferred coffee
[] Takeaways
[] Please like, share, and subscribe to our MLOps channels!
[] Creating his own team!
[] DevRel
[] The door dash of Europe
[] Data platform underneath
[] Cellular core deployment uses open source
[] Alibi
[] Kafka
[] Selling points to data scientists
[] Language models concerns of data scientists
[] Incorporating LLMs into the business
[] Feedback from data scientists and end users
[] User surveys
[] Evangelizing and giving talks
[] Tech Hub Culture in Berlin
[] Kubernetes lifestyle
[] Interacting with SREs
[] Wrap up
Taught by
MLOps.community
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