Feature Engineering with Python

"Feature Engineering with Python" is a practical guide that walks you through the entire feature engineering process-from understanding data to extracting, transforming, and selecting the most valuable features. With real-world case studies and hands-on coding examples in Python, this book equips you with the skills needed to turn data into a competitive advantage.
What You'll Learn:
✔ The fundamentals of feature engineering and its impact on machine learning models
✔ Techniques for handling missing data, outliers, and categorical variables
✔ Feature extraction methods for text, images, and time-series data
✔ Scaling, encoding, and transformation strategies for numerical and categorical features
✔ Feature selection techniques, including statistical methods and machine learning-based approaches
✔ How to automate feature engineering with Python libraries like Featuretools and Scikit-learn
✔ Best practices and case studies from industries such as finance, healthcare, and retail
Who This Book is For:
✅ Data Scientists and Machine Learning Engineers
✅ AI Researchers and Analysts
✅ Python Developers looking to enhance their ML skills
✅ Anyone interested in building better predictive models with well-crafted features
With hands-on examples and step-by-step guidance, "Feature Engineering with Python" empowers you to transform data into smarter machine learning models. Get ready to take your ML skills to the next level! 🚀

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