Overview
Syllabus
An Introduction to MLOps.
MLOps with Azure - Hands on Session.
Hands on Kubernetes for Data Scientists and Engineers.
MLOps with TFX pipelines - Tensorflow Extended.
MLOps - End to End automated CI/CD pipeline for Continuous Deployment.
Feature Store for Machine Learning - MLOps.
MLOps with Feature Store - Move models from development to production.
Accelerating Machine Learning with a Feature Store.
Model Monitoring - Concept and Data Drift - Part 2.
Model Monitoring Deep Dive.
Machine Learning Models - Load and Performance Testing Demo.
Model Deployment Deep Dive using Containers, Google Cloud Run and App Engine.
Model Deployment Challenges and Best Practices - Webinar for Analytics Vidhya.
MLOps - Machine Learning Deployment with CI/CD pipeline - Part 1.
MLOps - GitHub Kubernetes Continuous Model Deployment - Streamlit - Part 2.
Getting Started with Apache Airflow.
Taught by
AIEngineering
Reviews
5.0 rating, based on 1 Class Central review
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Course is very good to get overview of getting started with MLops. The panel was very experienced and with good handon material inorder to understand practical aspect of it.