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Book synopsis

Stop wasting hours cleaning messy datasets before they derail your machine learning projects
Python Scripts for Feature Engineering: Master Data Preparation gives you a practical, code driven framework for transforming raw data into high quality features ready for analytics and machine learning. Instead of relying on theory heavy explanations, this book focuses on real world workflows, reusable Python scripts, and proven techniques used throughout the data preparation process.
Learn to clean inconsistent datasets, engineer meaningful features, and automate preparation pipelines using Pandas, NumPy, and Scikit Learn. Every chapter is designed to help you move from raw data to model ready datasets with greater speed, accuracy, and confidence.
Build cleaner datasets and reduce data preparation time through repeatable workflows
Master feature creation, transformation, encoding, scaling, and dimensionality reduction techniques
Develop production ready data preparation pipelines that improve scalability and maintainability
Written for data scientists, machine learning engineers, analysts, developers, and technical professionals who need reliable feature engineering solutions in real world environments. Based on practical implementation experience and industry standard workflows used in modern data science projects.
You'll gain the exact techniques needed to prepare high quality data before poor feature design undermines your results

Book details

• Full title: Python Scripts for Feature Engineering
• Subtitle: Master Data Preparation: Foundations, Data Preparation, Feature Creation, and Dimensionality Reduction
• Author: Justin Benedict
• Language: English
• Binding: Paperback
• Number of pages: 398
• EAN: 9798181849655
• ID: 52900697
• Publisher: Independently published
• Weight: 920 g
• Dimensions: 280 × 216 × 21 mm
• Date of publishing: 16. June 2026

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