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Titlebook: Introducing HR Analytics with Machine Learning; Empowering Practitio Christopher M. Rosett,Austin Hagerty Book 2021 Springer Nature Switzer

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樓主: Garfield
31#
發(fā)表于 2025-3-26 23:21:13 | 只看該作者
32#
發(fā)表于 2025-3-27 02:34:43 | 只看該作者
Common Machine Learning Techniquesbuild and tune models, but rather an introduction to how these techniques work, curated for the novice data scientist or HR practitioner. Topics include linear and polynomial regression, logistic regression, K-nearest neighbors, SVM’s, decision trees, random forests (for classification and regressio
33#
發(fā)表于 2025-3-27 06:46:10 | 只看該作者
34#
發(fā)表于 2025-3-27 13:18:01 | 只看該作者
Machine Learning Project Managementchapter introduces project management from the machine learning perspective. For the current or future HR practitioner, this chapter explains why project management is important for machine learning projects and introduces how machine learning projects are different from other types of HR projects.
35#
發(fā)表于 2025-3-27 15:59:19 | 只看該作者
The 3 A’s of a Machine Learning Projectparing traditional project management frameworks from Chap. . (Waterfall and Agile) to a common machine learning-specific methodology in use today (CRISP-DM), this chapter introduces a unique take on project management, called “The Three A’s of a Machine Learning Project.” All machine learning proje
36#
發(fā)表于 2025-3-27 18:51:43 | 只看該作者
37#
發(fā)表于 2025-3-28 01:25:41 | 只看該作者
Bringing Your Model to Lifel development—illustrating the difference between finding and preparing data versus using it to build and tune a model. This chapter dives into the iterative nature of this process and shows the feedback loops that exist between the Appreciate and Assemble phases, as well as the feedback loops that
38#
發(fā)表于 2025-3-28 04:00:47 | 只看該作者
39#
發(fā)表于 2025-3-28 06:47:28 | 只看該作者
40#
發(fā)表于 2025-3-28 11:58:37 | 只看該作者
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