Nyd den ubegrænsede adgang til tusindvis af spændende e- og lydbøger - helt gratis
Fakta
Streamline data preprocessing and feature engineering in your machine learning project with this third edition of the Python Feature Engineering Cookbook to make your data preparation more efficient. This guide addresses common challenges, such as imputing missing values and encoding categorical variables using practical solutions and open source Python libraries. You’ll learn advanced techniques for transforming numerical variables, discretizing variables, and dealing with outliers. Each chapter offers step-by-step instructions and real-world examples, helping you understand when and how to apply various transformations for well-prepared data. The book explores feature extraction from complex data types such as dates, times, and text. You’ll see how to create new features through mathematical operations and decision trees and use advanced tools like Featuretools and tsfresh to extract features from relational data and time series. By the end, you’ll be ready to build reproducible feature engineering pipelines that can be easily deployed into production, optimizing data preprocessing workflows and enhancing machine learning model performance.
© 2024 Packt Publishing (E-bog): 9781835883594
Release date
E-bog: 30. august 2024
Over 600.000 titler
Download og nyd titler offline
Eksklusive titler + Mofibo Originals
Børnevenligt miljø (Kids Mode)
Det er nemt at opsige når som helst
For dig som vil prøve Mofibo.
1 konto
20 timer/måned
Eksklusivt indhold hver uge
Fri lytning til podcasts
Gem ubrugt tid
Ingen binding
For dig som lytter og læser ofte.
1 konto
100 timer/måned
Eksklusivt indhold hver uge
Fri lytning til podcasts
Ingen binding
For dig som lytter og læser ubegrænset.
1 konto
Ubegrænset adgang
Eksklusivt indhold hver uge
Fri lytning til podcasts
Ingen binding
For dig som ønsker at dele historier med familien.
2-6 konti
100 timer/måned pr. konto
Fri lytning til podcasts
Kun 39 kr. pr. ekstra konto
Ingen binding
2 konti
179 kr. /månedDansk
Danmark