[] Please like, share, leave a review, and subscribe to our MLOps channels!
4
[] Cody's work at Azure ML
5
[] LLM Data Engineering Evolution
6
[] The Ibis project
7
[] SQL verse data frames
8
[] Evolution of Ibis
9
[] Apache Arrow
10
[] "Open standards are a good idea"
11
[] How to create standards for AI quality
12
[] Network effect
13
[] "Open Periphery" concept explained
14
[24:29 - ] WandB Free Courses ad
15
[] Voltron Data users
16
[] Choosing data system consideration
17
[] Smooth transition with Ibis
18
[] Community requests for Ibis
19
[] Incorporate new tech wisely
20
[] Using LLMs for internal Queries
21
[] Tech news overload
22
[] BirdBrain explores SQL Series
23
[] Wrap up
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Grab it
Explore the importance of open standards in MLOps with Cody Peterson, Senior Technical Product Manager at Voltron Data, in this 46-minute podcast episode. Discover how open-source projects like Ibis and Apache Arrow are revolutionizing data handling, enabling scalability beyond traditional tools like pandas. Learn about the benefits of composable data systems, avoiding vendor lock-in, and keeping costs low. Gain insights into the evolution of data engineering, the role of SQL versus data frames, and the concept of "Open Periphery" in building next-generation data systems. Understand how open standards can break down silos in real-world engineering teams and improve collaboration in machine learning projects.
Open Standards Make MLOps Easier and Silos Harder - MLOps Podcast Episode 234