MLOps, short for Machine Learning Operations, refers to the practice of applying DevOps principles to machine learning. This MLOps course will guide you through an end-to-end MLOps project, covering everything from data ingestion to deployment, using state-of-the-art tools like ZenML, MLflow, and various MLOps libraries.
? Code: https://github.com/ayush714/mlops-projects-course/tree/main
✏️ Course created by @AyushSinghSh
⭐️ Contents ⭐️
⌨️ (0:00:00) Intro
⌨️ (0:01:28) MLOps Fundamentals (introduction to mlops)
⌨️ (0:32:54) Fundamentals of Zenml
⌨️ (0:45:31) Customer Satisfaction project
⌨️ (0:45:51) Dataset of Olist customer dataset
⌨️ (0:49:01) Installing necessary libraries
⌨️ (0:55:01) Creating blueprint of steps
⌨️ (1:08:06) Zenml Dashboard
⌨️ (1:13:46) Implementing steps
⌨️ (1:15:01) Working on data cleaning
⌨️ (1:33:41) Working on model development
⌨️ (1:41:09) Working on evaluation model
⌨️ (1:48:36) Run pipeline
⌨️ (1:54:28) Implementing experiment tracker
⌨️ (2:11:02) Deployment pipeline
⌨️ (2:58:08) Streamlit app
? Thanks to our Champion and Sponsor supporters:
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? Nattira Maneerat
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? Justin Hual
? Otis Morgan
? Oscar Rahnama
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