Agile Machine Learning: (Record no. 694601)
[ view plain ]
000 -LEADER | |
---|---|
fixed length control field | 02375nam a2200181 4500 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9781484276785 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 006.31 |
Item number | CAR |
084 ## - OTHER CLASSIFICATION NUMBER | |
Source of Number | Colon Classification |
100 ## - MAIN ENTRY--AUTHOR NAME | |
Personal name | Carter, Eric |
245 ## - TITLE STATEMENT | |
Title | Agile Machine Learning: |
Sub Title | Effective Machine Learning Inspired by the Agile Manifesto/ |
Statement of responsibility, etc | Eric Carter, Matthew Hurst |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
Place of publication | California: |
Name of publisher | Apress, |
Year of publication | 2019. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | xvii, 248 p. |
520 ## - SUMMARY, ETC. | |
Summary, etc | Build resilient applied machine learning teams that deliver better data products through adapting the guiding principles of the Agile Manifesto.<br/><br/>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.<br/><br/>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.<br/> What You'll Learn<br/><br/> Effectively run a data engineering team that is metrics-focused, experiment-focused, and data-focused<br/> Make sound implementation and model exploration decisions based on the data and the metrics<br/> Know the importance of data wallowing: analyzing data in real time in a group setting<br/> Recognize the value of always being able to measure your current state objectively<br/> Understand data literacy, a key attribute of a reliable data engineer, from definitions to expectations<br/><br/><br/>Who This Book Is For<br/><br/>Anyone who manages a machine learning team, or is responsible for creating production-ready inference components. Anyone responsible for data project workflow of sampling data; labeling, training, testing, improving, and maintaining models; and system and data metrics will also find this book useful. Readers should be familiar with software engineering and understand the basics of machine learning and working with data. |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical Term | Agile Machine Learning |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical Term | Applied machine learning |
700 ## - ADDED ENTRY--PERSONAL NAME | |
Personal name | Hurst, Matthew |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | Book |
Withdrawn status | Lost status | Damaged status | Not for loan | Home Library | Current Location | Shelving location | Date acquired | Full call number | Accession Number | Price effective from | Koha item type |
---|---|---|---|---|---|---|---|---|---|---|---|
Dept. of Futures Studies | Dept. of Futures Studies | General Stacks | 01/08/2023 | 006.31 CAR | DFS4614 | 01/08/2023 | Book |