Machine Learning Engineering with MLflow
Machine Learning Engineering with MLflow is a step-by-step guide that will have you up and running, and productive in no time with MLflow using the most effective machine learning engineering approach. You will also learn how to scale MLflow in big data environments and for high computing demands.
Offered by
Difficulty Level
Intermediate
Completion Time
8h16m
Language
English
About Book
Who Is This Book For?
This book is for data scientists, machine learning engineers, and data engineers who want to gain hands-on machine learning engineering experience and learn how they can manage an end-to-end machine learning life cycle with the help of MLflow. Intermediate-level knowledge of the Python programming language is expected.
Machine Learning Engineering with MLflow
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 8h16m total length
Introducing MLflow
Your Machine Learning Project
Your Data Science Workbench
Experiment Management in MLflow
Managing Models with MLflow
Introducing ML Systems Architecture
Data and Feature Management
Training Models with MLflow
Deployment and Inference with MLflow
Scaling Up Your Machine Learning Workflow
Performance Monitoring
Advanced Topics with MLflow
Related Resources
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