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Explore the concept of MLOps in this 29-minute conference talk that delves into its impact on the industry and the challenges of building real-world AI systems. Learn about the importance of open-source tools and standardization in MLOps, and discover why a combination of software engineering, data engineering, and machine learning engineering is crucial for success. Gain insights into applied AI and its practical implications through a comprehensive overview of MLOps principles and best practices.
Syllabus
Intro
Quick Intro
Effects on the Industry
Applied Al - Challenges of building real-world Systems
What is MLOpe? My Take
#2 Use open source and standardize
#3 Software/Data/ML Engineering is key to succeed
Summarized Talk
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WeAreDevelopers