Python 3 and feature engineering:
This book is designed for data scientists, machine learning practitioners, and anyone with a foundational understanding of Python 3.x. In the evolving field of data science, the ability to manipulate and understand datasets is crucial. The book offers content for mastering these skills using Python...
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Dulles, VA
Mercury Learning and Information
[2023]
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| Subjects: | |
| Links: | https://doi.org/10.1515/9781683929482 https://doi.org/10.1515/9781683929482 https://doi.org/10.1515/9781683929482 https://doi.org/10.1515/9781683929482 https://doi.org/10.1515/9781683929482 https://doi.org/10.1515/9781683929482 https://doi.org/10.1515/9781683929482 https://doi.org/10.1515/9781683929482 https://doi.org/10.1515/9781683929482 https://doi.org/10.1515/9781683929482 https://doi.org/10.1515/9781683929482 |
| Summary: | This book is designed for data scientists, machine learning practitioners, and anyone with a foundational understanding of Python 3.x. In the evolving field of data science, the ability to manipulate and understand datasets is crucial. The book offers content for mastering these skills using Python 3. The book provides a fast-paced introduction to a wealth of feature engineering concepts, equipping readers with the knowledge needed to transform raw data into meaningful information. Inside, you'll find a detailed exploration of various types of data, methodologies for outlier detection using Scikit-Learn, strategies for robust data cleaning, and the intricacies of data wrangling. The book further explores feature selection, detailing methods for handling imbalanced datasets, and gives a practical overview of feature engineering, including scaling and extraction techniques necessary for different machine learning algorithms. It concludes with a treatment of dimensionality reduction, where you'll navigate through complex concepts like PCA and various reduction techniques, with an emphasis on the powerful Scikit-Learn framework |
| Physical Description: | 1 Online-Ressource (216 Seiten) |
| ISBN: | 9781683929482 |
| DOI: | 10.1515/9781683929482 |
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| isbn | 9781683929482 |
| language | English |
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| publishDate | 2023 |
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| publisher | Mercury Learning and Information |
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| spellingShingle | Campesato, Oswald Python 3 and feature engineering COMPUTERS / Desktop Applications / Spreadsheets bisacsh |
| title | Python 3 and feature engineering |
| title_auth | Python 3 and feature engineering |
| title_exact_search | Python 3 and feature engineering |
| title_full | Python 3 and feature engineering Oswald Campesato |
| title_fullStr | Python 3 and feature engineering Oswald Campesato |
| title_full_unstemmed | Python 3 and feature engineering Oswald Campesato |
| title_short | Python 3 and feature engineering |
| title_sort | python 3 and feature engineering |
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