Python Feature Engineering Cookbook

Feature engineering is a critical step in developing successful machine learning models. In 'Python Feature Engineering Cookbook', you will explore practical recipes for generating, selecting, and transforming features using Python. By the end, you'll have the skills to automate feature engineering and enhance your data preparation workflow.

What this Book will help me do

• Simplify feature pipelines with Python libraries like pandas and scikit-learn.
• Impute missing data and encode categorical variables effectively.
• Derive new features and transform existing ones with advanced techniques.
• Gain expertise in handling time series and text data in your models.
• Learn scalable methods for feature extraction and engineering.

Author(s)

None Galli is an experienced data scientist and mentor specializing in practical machine learning applications. With a passion for teaching, None has created content that distills complex topics into actionable knowledge. Drawing from years in the field, their approach emphasizes real-world utility and clarity of instruction.

Who is it for?

This book is ideal for machine learning practitioners who want to enhance model performance through improved features. Whether you're a data scientist aiming to streamline workflows or an engineer specializing in AI, this resource offers value. Readers should have a basic understanding of Python and machine learning concepts to fully benefit. Its accessible content makes it a go-to guide for diverse learners seeking expertise in feature engineering.