Python 3 and Feature Engineering

• Main Author: Campesato, Oswald
• Format: eBook
• Language: English
• Published: Berlin Mercury Learning & Information 2023; Mercury Learning and Information
• Edition: 1
• Subjects: COMPUTERS / Desktop Applications / Spreadsheets; data science, machine learning, Python, datasets, data wrangling, awk, artificial intelligence; Python (Computer program language); data science, machine learning, Python, datasets, data wrangling, awk, artificial intelligence
• ISBN: 9781683929499; 1683929497
• DOI: 10.1515/9781683929482

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.