Python 3 and Feature Engineering / / Oswald Campesato.

• Superior document: Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE 2023 English
• VerfasserIn: Campesato, Oswald,
• Place / Publishing House: Dulles, VA : : Mercury Learning and Information, , [2023]; ©2023
• Year of Publication: 2023
• Language: English
• Physical Description: 1 online resource (216 p.)

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.

Table of Contents

Frontmatter -- Contents -- Preface -- Chapter 1: Working With Datasets -- Chapter 2: Outlier and Anomaly Detection -- Chapter 3: Data Cleaning Tasks -- Chapter 4: Data Wrangling -- Chapter 5: Feature Selection -- Chapter 6: Feature Engineering -- Chapter 7: Dimensionality Reduction -- Appendix: Working With awk -- Index