Scaling AI in Production

Name: Scaling%20AI%20in%20Production
Uploaded: 2021-05-19

Posted May 19, 2021 | Views 621

# Machine Learning

# ML Systems

# AI

# AIEngineering

# bit.ly/AIEngineering

speakers

Srivatsan Srinivasan

Chief Data Scientist @ AIEngineering

20+ years of intense passion for building data-driven applications and products for top financial customers. Srivatsan has been a trusted advisor to a senior-level executive from business and technology, helping them with complex transformation in the data and analytics space. Srivatsan also run a YouTube Channel (AIEngineering) where he talks about data, AI and MLOps.

+ Read More

Demetrios Brinkmann

Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

+ Read More

Vishnu Rachakonda

Data Scientist @ Firsthand

Vishnu Rachakonda is the operations lead for the MLOps Community and co-hosts the MLOps Coffee Sessions podcast. He is a machine learning engineer at Tesseract Health, a 4Catalyzer company focused on retinal imaging. In this role, he builds machine learning models for clinical workflow augmentation and diagnostics in on-device and cloud use cases. Since studying bioengineering at Penn, Vishnu has been actively working in the fields of computational biomedicine and MLOps. In his spare time, Vishnu enjoys suspending all logic to watch Indian action movies, playing chess, and writing.

+ Read More

SUMMARY

This Coffee Session is a Collaboration with @AIEngineering. Srivatsan Srinivasan, the founder of the popular AI Engineering channel on YouTube and a senior partner at a major technology consultancy. Sri has a true passion for building ML systems and his channel engages in some of the most detailed, thorough, and complete treatments of the MLOps topics we often discuss in the community. It's no surprise then, that his coffee session with us went similarly! This conversation became pretty technical. We delved into details of how to set up CI/CD, how to set up the right kinds of tests, which cloud tools stand out to us on GCP, AWS, etc., and many other topics. Sri was a wealth of knowledge on all these fronts! Some tidbits: 1. Fail smart, not just fast. 2. Deploy a useless model over waiting to deploy the perfect model 3. Understand that much of DevOps/Kubernetes/CI/CD is YAML proficiency, which can be intimidating, but not impossibly by any means. 4. AutoML has a ton of potential that all of us are eagerly watching out for. 5. Avoid overengineering ML systems by doing things as simply as possible. We know many of you have been waiting for a more technical approach to some coffee sessions, and I think this is what you want! Let us know your thoughts on some of the practical tips we discussed (especially about CI/CD and testing).

+ Read More