Agile Machine Learning Effective Machine Learning Inspired by the Agile Manifesto /

• Main Authors: Carter, Eric (Author, http://id.loc.gov/vocabulary/relators/aut), Hurst, Matthew (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berkeley, CA : Apress : Imprint: Apress, 2019.
• Edition: 1st ed. 2019.
• Subjects: Microsoft software.; Microsoft .NET Framework.; Software engineering.; Big data.; Microsoft and .NET.; Software Engineering.; Big Data.

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 e...

Table of Contents:

• Chapter 1: Early Delivery
• Chapter 2: Changing Requirements
• Chapter 3: Continuous Delivery
• Chapter 4: Aligning with the Business
• Chapter 5: Motivated Individuals
• Chapter 6: Effective Communication
• Chapter 7: Monitoring
• Chapter 8: Sustainable Development
• Chapter 9: Technical Excellence
• Chapter 10 Simplicity
• Chapter 11: Self-organizing Teams
• Chapter 12: Tuning and Adjusting
• Chapter 13: Conclusion.