Dive into a comprehensive crash course on MLOps for beginners, designed for data scientists with basic knowledge of developing machine learning models in Jupyter Notebooks. Explore the concept of MLOps, its importance, and learn how to create and deploy a fully reproducible machine learning pipeline from scratch. Gain insights into continuous training, drift detection, alerts, and model deployment. Discover the realities of data science beyond notebooks, understanding the value creation process in production environments. Follow along with a practical demo using ZenML and acquire essential skills to bridge the gap between model development and real-world implementation.
Overview
Syllabus
Introduction
About MLOps
Machine Learning in Production
Post-deployment Woes
Models Go Stale
Model Centric vs Data Centric
Takeaway
Demo on ZenML
Taught by
Data Science Dojo
