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Cleaning Data for Effective Data Science

(ebook) (audiobook) (audiobook) Język publikacji: angielski
Autor:
David Mertz
Cleaning Data for Effective Data Science David Mertz - okładka książki

Cleaning Data for Effective Data Science David Mertz - okładka książki

Cleaning Data for Effective Data Science David Mertz - okładka audiobooka MP3

Cleaning Data for Effective Data Science David Mertz - okładka audiobooks CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
498
Dostępne formaty:
     PDF
     ePub
     Mobi

Ebook

129,00 zł

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Data cleaning is the all-important first step to successful data science, data analysis, and machine learning. If you work with any kind of data, this book is your go-to resource, arming you with the insights and heuristics experienced data scientists had to learn the hard way.

In a light-hearted and engaging exploration of different tools, techniques, and datasets real and fictitious, Python veteran David Mertz teaches you the ins and outs of data preparation and the essential questions you should be asking of every piece of data you work with.

Using a mixture of Python, R, and common command-line tools, Cleaning Data for Effective Data Science follows the data cleaning pipeline from start to end, focusing on helping you understand the principles underlying each step of the process. You'll look at data ingestion of a vast range of tabular, hierarchical, and other data formats, impute missing values, detect unreliable data and statistical anomalies, and generate synthetic features. The long-form exercises at the end of each chapter let you get hands-on with the skills you've acquired along the way, also providing a valuable resource for academic courses.

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