Managing Machine Learning Projects

by Simon Thompson

Released July 2023

Publisher(s): Manning Publications

ISBN: None

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Audiobook description

Guide machine learning projects from design to production with the techniques in this one-of-a-kind project management guide. No ML skills required

In Managing Machine Learning Projects you’ll learn essential machine learning project management techniques, including:

Understanding an ML project’s requirements
Setting up the infrastructure for the project and resourcing a team
Working with clients and other stakeholders
Dealing with data resources and bringing them into the project for use
Handling the lifecycle of models in the project
Managing the application of ML algorithms
Evaluating the performance of algorithms and models
Making decisions about which models to adopt for delivery
Taking models through development and testing
Integrating models with production systems to create effective applications
Steps and behaviors for managing the ethical implications of ML technology

Managing Machine Learning Projects is an end-to-end guide for delivering machine learning applications on time and under budget. It lays out tools, approaches, and processes designed to handle the unique challenges of machine learning project management. You’ll follow an in-depth case study through a series of sprints and see how to put each technique into practice. The book’s strong consideration to data privacy, and community impact ensure your projects are ethical, compliant with global legislation, and avoid being exposed to failure from bias and other issues.

About the Technology
Ferrying machine learning projects to production often feels like navigating uncharted waters. From accounting for large data resources to tracking and evaluating multiple models, machine learning technology has radically different requirements than traditional software. Never fear! This book lays out the unique practices you’ll need to ensure your projects succeed.

About the Book
Managing Machine Learning Projects is an amazing source of battle-tested techniques for effective delivery of real-life machine learning solutions. The book is laid out across a series of sprints that take you from a project proposal all the way to deployment into production. You’ll learn how to plan essential infrastructure, coordinate experimentation, protect sensitive data, and reliably measure model performance. Many ML projects fail to create real value—read this book to make sure your project is a success.

What's Inside

Set up infrastructure and resource a team
Bring data resources into a project
Accurately estimate time and effort
Evaluate which models to adopt for delivery
Integrate models into effective applications

About the Reader
For anyone interested in better management of machine learning projects. No technical skills required.

About the Author
Simon Thompson has spent 25 years developing AI systems to create applications for use in telecoms, customer service, manufacturing and capital markets. He led the AI research program at BT Labs in the UK, and is now the Head of Data Science at GFT Technologies.

Quotes
Provides many examples of practical implementation issues including scoping, sprints, case studies, and request tickets.
- Abi Aryan, MLOps Podcast

Golden for all managers, even those with a less technical background. Lucid concept explanations.
- Amrita Sarkar, Thomson Reuters

Years of experience boiled down to workable checklists, handy anecdotes, and guidance on regulatory and legal frameworks. Ignore at your peril.
- Dan Gilks, British Telecommunications