Agile Machine Learning
- Paperback: 248 pages
- Publisher: WOW! eBook; 1st edition (November 3, 2019)
- Language: English
- ISBN-10: 1484251067
- ISBN-13: 978-1484251065
Agile Machine Learning: Effective Machine Learning Inspired by the Agile Manifesto
Build resilient applied machine learning teams that deliver better data products through adapting the guiding principles of the Agile Manifesto.
Bringing together talented people to create a great applied machine learning team is no small feat. With developers and data scientists both contributing expertise in their respective fields, communication alone can be a challenge. Agile Machine Learning teaches you how to deliver superior data products through agile processes and to learn, by example, how to organize and manage a fast-paced team challenged with solving novel data problems at scale, in a production environment.
What You’ll Learn
- Effectively run a data engineering team that is metrics-focused, experiment-focused, and data-focused
- Make sound implementation and model exploration decisions based on the data and the metrics
- Know the importance of data wallowing: analyzing data in real time in a group setting
- Recognize the value of always being able to measure your current state objectively
- Understand data literacy, a key attribute of a reliable data engineer, from definitions to expectations
The authors’ approach models the ground-breaking engineering principles described in the Agile Manifesto. The book provides further context, and contrasts the original principles with the requirements of systems that deliver a data product.