Data Preparation for Machine Learning: Data Cleaning, Feature Selection, and Data Transforms in Python

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Machine Learning Mastery, 30 de jun. de 2020 - 398 páginas

Data preparation involves transforming raw data in to a form that can be modeled using machine learning algorithms. Cut through the equations, Greek letters, and confusion, and discover the specialized data preparation techniques that you need to know to get the most out of your data on your next project. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently and effectively prepare your data for predictive modeling with machine learning.


 

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Conteúdo

III Data Cleaning
37
IV Feature Selection
110
V Data Transforms
212
VI Advanced Transforms
316
VII Dimensionality Reduction
337
VIII Appendix
369
IX Conclusions
380
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Sobre o autor (2020)

Jason Brownlee, Ph.D. is a machine learning specialist who teaches developers how to get results with modern machine learning and deep learning methods via hands-on tutorials. 

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