#71 Scaling Machine Learning Adoption: A Pragmatic Approach

DataFramed

In this episode of DataFramed, we speak with Noah Gift, founder of Pragmatic AI Labs and prolific author about operationalizing machine learning in organizations and his new book Practical MLOPs.

Throughout the episode, Noah discusses his background, his philosophy around pragmatic AI, the differences between data science in academia and the real world, how data scientists can become more action-oriented by creating solutions that solve real-world problems, the importance of dev-ops, his most recent book on the practical guide to MLOps, how data science can be compared to Brazilian jiu-jitsu, what data scientists should learn to scale the amount of value they deliver, his thoughts on auto-ml and automation, and more.

Relevant links from the interview:

• We’d love your feedback! Let us know which topics you’d like us to cover and what you think of DataFramed by answering this 30-second survey
• Unsettled: What Climate Science Tells Us, What It Doesn't, and Why It Matters
• Check out Noah's books
• Check out Noah's course on DataCamp
• Connect with Noah on LinkedIn
• Gain access to DataCamp's full course library at a discount!