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1
Introduction
2
About MLOps
3
Machine Learning in Production
4
Post-deployment Woes
5
Models Go Stale
6
Model Centric vs Data Centric
7
Takeaway
8
Demo on ZenML
Description:
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.

MLOps Crash Course for Beginners

Data Science Dojo
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