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Python feature engineering cookbook /
Feature engineering, the process of transforming variables and creating features, albeit time-consuming, ensures that your machine learning models perform seamlessly. This second edition of Python Feature Engineering Cookbook will take the struggle out of feature engineering by showing you how to us...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing Ltd.,
2022.
|
| Edición: | Second edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a22000007i 4500 | ||
|---|---|---|---|
| 001 | KNOVEL_on1350412247 | ||
| 003 | OCoLC | ||
| 005 | 20231027140348.0 | ||
| 006 | m o d | ||
| 007 | cr cnu|||unuuu | ||
| 008 | 221108s2022 enka o 001 0 eng d | ||
| 040 | |a ORMDA |b eng |e rda |e pn |c ORMDA |d OCLCF |d OCLCO | ||
| 020 | |z 9781804611302 | ||
| 035 | |a (OCoLC)1350412247 | ||
| 037 | |a 9781804611302 |b O'Reilly Media | ||
| 050 | 4 | |a QA76.73.P98 | |
| 082 | 0 | 4 | |a 005.13/3 |2 23/eng/20221108 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Galli, Soledad, |e author. | |
| 245 | 1 | 0 | |a Python feature engineering cookbook / |c Soledad Galli. |
| 250 | |a Second edition. | ||
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing Ltd., |c 2022. | |
| 300 | |a 1 online resource (386 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a Includes index. | ||
| 520 | |a Feature engineering, the process of transforming variables and creating features, albeit time-consuming, ensures that your machine learning models perform seamlessly. This second edition of Python Feature Engineering Cookbook will take the struggle out of feature engineering by showing you how to use open source Python libraries to accelerate the process via a plethora of practical, hands-on recipes. This updated edition begins by addressing fundamental data challenges such as missing data and categorical values, before moving on to strategies for dealing with skewed distributions and outliers. The concluding chapters show you how to develop new features from various types of data, including text, time series, and relational databases. With the help of numerous open source Python libraries, you'll learn how to implement each feature engineering method in a performant, reproducible, and elegant manner. By the end of this Python book, you will have the tools and expertise needed to confidently build end-to-end and reproducible feature engineering pipelines that can be deployed into production. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 590 | |a Knovel |b ACADEMIC - Software Engineering | ||
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Application software |x Development. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 6 | |a Logiciels d'application |x Développement. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 7 | |a Application software |x Development |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Python (Computer program language) |2 fast | |
| 856 | 4 | 0 | |u https://appknovel.uam.elogim.com/kn/resources/kpPFEC0004/toc |z Texto completo |
| 994 | |a 92 |b IZTAP | ||