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Feature Engineering for Machine Learning:

Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists. Alice Zheng, Amanda Casari

Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists


Feature.Engineering.for.Machine.Learning.Principles.and.Techniques.for.Data.Scientists.pdf
ISBN: 9781491953242 | 214 pages | 6 Mb


Download Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists



Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists Alice Zheng, Amanda Casari
Publisher: O'Reilly Media, Incorporated



Paperback, 9781491953242, 1491953241. Feature Engineering for Machine Learning Models. Basic knowledge of machine learning techniques (i.e. Machine Learning works best with well formed data.Feature engineering describes certain techniques to make sure we're working with the best possible representation of the data we collected. Feature Engineering for Machine Learning Models: Principles and Techniquesfor Data Scientists by Alice Zheng. Following are twotechniques of feature engineering: scaling and selection. Classification, regression, and clustering). The quality, amount, preparation, and selection of data is critical to the success of a machine learning solution. Understand machine learning principles (training, validation, etc. ) Knowledge of data query and data processing tools (i.e. Ľ�者: Alice Zheng 出版社: O′Reilly 原作名: MasteringFeature Engineering Principles and Techniques for Data Scientists 出版年: 2017- 12-31 页数: 200 定价: GBP 34.50 装帧: Paperback ISBN: 9781491953242. Vijfhart biedt u de cursus Perform Cloud Data Science with Azure MachineLearning (M20774) aan. Feature Engineering forMachine Learning Models. Click here for the lowest price!



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