Explore the journey from Jupyter notebooks to production-ready machine learning systems in this 30-minute conference talk by Tomas Fernandez at Conf42 ML 2024. Discover the importance of MLOps and its role in bridging the gap between data science experimentation and real-world deployment. Gain insights through practical demonstrations showcasing key MLOps concepts and best practices. Learn how to streamline the process of moving machine learning models from development to production environments, ensuring scalability, reproducibility, and maintainability.
Overview
Syllabus
intro
preamble
why mlops?
demos
thank you!
Taught by
Conf42
