661: Designing Machine Learning Systems

Chip Huyen, co-founder of Claypot AI and author of O'Reilly's best-selling "Designing Machine Learning Systems" is here to share her expertise on designing production-ready machine learning applications, the importance of iteration in real-world deployment, and the critical role of real-time machine learning in various applications. Technical listeners like data scientists and machine learning engineers will definitely enjoy this one!

This episode is brought to you by Pathway, the reactive data processing framework (https://www.pathway.com/?from=superdatascience), and by epic LinkedIn Learning instructor Keith McCormick(linkedin.com/learning/instructors/keith-mccormick). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:

• Why Chip wrote 'Designing Machine Learning Systems' [08:58]

• How Chip ended up teaching at Stanford [13:18]

• About Chip's book 'Designing Machine Learning Systems' [21:12]

• What makes ML feel like magic [30:53]

• How to align business intent, context, and metrics with ML [37:55]

• The lessons Chip learned about training data [42:03]

• Chip's secrets to engineering good features [53:19]

• How Chip optimizes her productivity [1:07:48]

Additional materials: www.superdatascience.com/661