MLOps.community
Ein Podcast von Demetrios
430 Folgen
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Deep in the heart of data // Carl Steinbach // MLOps Coffee Sessions #22
Vom: 18.12.2020 -
When machine learning meets privacy - Episode 7
Vom: 17.12.2020 -
When Machine Learning meets privacy - Episode 6
Vom: 14.12.2020 -
Human-centric ML Infrastructure: A Netflix Original // Savin Goyal // MLOps Meetup #44
Vom: 14.12.2020 -
A Conversation with Seattle Data Guy // Benjamin Rogojan // MLOps Coffee Sessions #21
Vom: 8.12.2020 -
Monzo Bank - An MLOps Case Study // Neal Lathia // MLOps Coffee Sessions #20
Vom: 7.12.2020 -
When Machine Learning meets privacy - Episode 5
Vom: 3.12.2020 -
When Machine Learning meets privacy - Episode 4
Vom: 26.11.2020 -
Introducing Data Downtime: From Firefighting to Winning // Barr Moses // MLOps Coffee Sessions #19
Vom: 24.11.2020 -
The Current MLOps Landscape // Nathan Benaich & Timothy Chen // MLOps Meetup #43
Vom: 23.11.2020 -
When Machine Learning meets privacy - Episode 3 with Charles Radclyffe
Vom: 19.11.2020 -
UN Global Platform // Mark Craddock // Co-Founder & CTO, Global Certification and Training Ltd // MLOps Meetup #42
Vom: 16.11.2020 -
When Machine Learning meets Data Privacy - Episode 2 with Cat Coode
Vom: 12.11.2020 -
When You Say Data Scientist Do You Mean Data Engineer? Lessons Learned From Start Up Life // Elizabeth Chabot
Vom: 10.11.2020 -
Metaflow: Supercharging Our Data Scientist Productivity // Ravi Kiran Chirravuri // MLOps Meetup #41
Vom: 10.11.2020 -
Luigi in Production // MLOps Coffee Sessions #18 // Luigi Patruno ML in Production
Vom: 9.11.2020 -
When Machine Learning meets Data Privacy
Vom: 5.11.2020 -
Analyzing the Google Paper on Continuous Delivery in ML // Part 4 // MLOps Coffee Sessions #17
Vom: 3.11.2020 -
Hands-on serving models using KFserving // Theofilos Papapanagiotou // Data Science Architect at Prosus // MLOps Meetup #40
Vom: 30.10.2020 -
Operationalize Open Source Models with SAS Open Model Manager // Ivan Nardini // Customer Engineer at SAS // MLOps Meetup #39
Vom: 27.10.2020
Relaxed Conversations around getting AI into production, whatever shape that may come in (agentic, traditional ML, LLMs, Vibes, etc)