Автор: Eric Carter, Matthew Hurst
Издательство: Apress
Год: 2019
Формат: true pdf/epub/mobi
Страниц: 248
Размер: 11.5 Mb
Язык: English
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.
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.
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