LLC Feature Engineering for Modern Machine Learning with Scikit-Learn

Mastering data preparation and transformation for robust ML models
1. Auflage 2025
ISBN: 978-1-83702-670-8
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 436 Seiten

No detailed description available for "Feature Engineering for Modern Machine Learning with Scikit-Learn".

Autoren/Hrsg.

LLC, Cuantum Technologies

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Warehouse
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen

Inhaltsverzeichnis

Table of Contents - Real-World Data Analysis Projects
- Feature Engineering for Predictive Models
- Automating Feature Engineering with Pipelines
- Feature Engineering for Model Improvement
- Advanced Model Evaluation Techniques
- Introduction to Feature Selection with Lasso and Ridge
- Feature Engineering for Deep Learning
- AutoML and Automated Feature Engineering

Über Autor(innen)

LLC Cuantum Technologies:
Cuantum Technologies is a leading innovator in the realm of software development and education, with a special focus on leveraging the power of Artificial Intelligence and cutting-edge technology. They specialize in web-based software development, authoring insightful programming and AI literature, and building captivating web experiences with the intricate use of HTML, CSS, JavaScript, and Three.js. Their diverse array of products includes CuantumAI, a pioneering SaaS offering, and an array of books spanning from Python, NLP, PHP, JavaScript, and beyond. Through their services, they are constantly striving to demystify AI and technology, making it accessible, understandable, and useable for all.