000			02375nam a2200181 4500
020			_a9781484276785
082			_a006.31 _bCAR
084			_2Colon Classification
100			_aCarter, Eric
245			_aAgile Machine Learning: _bEffective Machine Learning Inspired by the Agile Manifesto/ _cEric Carter, Matthew Hurst
260			_aCalifornia: _bApress, _c2019.
300			_axvii, 248 p.
520			_aBuild 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 Who This Book Is For 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			_aAgile Machine Learning
650			_aApplied machine learning
700			_aHurst, Matthew
942			_cBK
999			_c694601 _d694601