E-book details

Machine Learning Engineering with MLflow. Manage the end-to-end machine learning life cycle with MLflow

Machine Learning Engineering with MLflow. Manage the end-to-end machine learning life cycle with MLflow

Natu Lauchande

Ebook
MLflow is a platform for the machine learning life cycle that enables structured development and iteration of machine learning models and a seamless transition into scalable production environments.
This book will take you through the different features of MLflow and how you can implement them in your ML project. You will begin by framing an ML problem and then transform your solution with MLflow, adding a workbench environment, training infrastructure, data management, model management, experimentation, and state-of-the-art ML deployment techniques on the cloud and premises. The book also explores techniques to scale up your workflow as well as performance monitoring techniques. As you progress, you’ll discover how to create an operational dashboard to manage machine learning systems. Later, you will learn how you can use MLflow in the AutoML, anomaly detection, and deep learning context with the help of use cases. In addition to this, you will understand how to use machine learning platforms for local development as well as for cloud and managed environments. This book will also show you how to use MLflow in non-Python-based languages such as R and Java, along with covering approaches to extend MLflow with Plugins.
By the end of this machine learning book, you will be able to produce and deploy reliable machine learning algorithms using MLflow in multiple environments.
  • 1. Introducing MLflow
  • 2. Your Machine Learning Project
  • 3. Your Data Science Workbench
  • 4. Experiment Management in MLflow
  • 5. Managing Models with MLflow
  • 6. Introducing ML Systems Architecture
  • 7. Data and Feature Management
  • 8. Training Models with MLflow
  • 9. Deployment and Inference with MLflow
  • 10. Scaling Up Your Machine Learning Workflow
  • 11. Performance Monitoring
  • 12. Advanced Topics with MLflow
  • Title: Machine Learning Engineering with MLflow. Manage the end-to-end machine learning life cycle with MLflow
  • Author: Natu Lauchande
  • Original title: Machine Learning Engineering with MLflow. Manage the end-to-end machine learning life cycle with MLflow
  • ISBN: 9781800561694, 9781800561694
  • Date of issue: 2021-08-27
  • Format: Ebook
  • Item ID: e_2a8r
  • Publisher: Packt Publishing