Sign in
Sign in or Join the community to continue

Practical MLOps Part 2

Posted Jun 02, 2021 | Views 682
# DevOps
# Machine Learning
Share

Speakers

user's Avatar
Alfredo Deza
Author, Speaker

Alfredo Deza is a passionate software engineer, speaker, author, and former Olympic athlete. With almost two decades of DevOps and software engineering experience, he teaches Machine Learning Engineering and gives lectures around the world about software development, personal development, and professional sports.

Alfredo has written several books about DevOps and Python including Python For DevOps and Practical MLOps. He continues to share his knowledge about resilient infrastructure, testing, and robust development practices in courses, books, and presentations.

Alfredo Deza is the author of Python for DevOps and Practical MLOps.

+ Read More
user's Avatar
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

SUMMARY

In this episode, the MLOps community talks about the importance of bringing DevOps principles and discipline into Machine Learning. Alfredo explains insights around creating the MLOps role, automation, constant feedback loops, and the number one objective - to ship Machine Learning models into production. Additionally, we covered some aspects of getting started with Machine Learning that is critical, in particular how democratization ML knowledge is critical to a better environment, from libraries to courses, to production results. Spreading the knowledge is key!

+ Read More

Watch More

Practical MLOps, Doing MLOps
Posted Jan 27, 2021 | Views 1.1K
# ML in Production
# Machine Learning
# Pragmatic AI Labs
# Paiml.com
MLOps Engineering Labs Recap Part 2
Posted Mar 02, 2021 | Views 626
# Open Source
# Panel
# Model Serving
# Interview
Building an Open Source MLOps Stack with ZenML Part 2
Posted Dec 14, 2022 | Views 895
# MLOps Stack
# Open Source
# ZenML
# Zenml.io