Machine Learning for Tabular Data
Seiten
2025
Manning Publications (Verlag)
978-1-63343-854-5 (ISBN)
Manning Publications (Verlag)
978-1-63343-854-5 (ISBN)
Business runs on tabular data in databases, spreadsheets, and logs. Crunch that data using deep learning, gradient boosting, and other machine learning techniques.
Every organization in the world stores data in tables. Advanced Analytics for Business reveals practical techniques for applying machine learning techniques like deep learning and gradient boosting to your company's rows and columns.
Inside Advanced Analytics for Business you'll learn how to:
Pick the right machine learning approach for your data
Apply deep learning to tabular data
Deploy tabular machine learning locally and in the cloud
Pipelines to automatically train and maintain a model
This book collects best practices, hard-won tips and tricks, and hands-on techniques for making sense of tabular data using advanced machine learning techniques. Inside, you'll discover how to use XGBoost and LightGBM on tabular data, optimize deep learning libraries like TensorFlow and PyTorch for tabular data, and use cloud tools like Vertex AI to create an automated MLOps pipeline.
Every organization in the world stores data in tables. Advanced Analytics for Business reveals practical techniques for applying machine learning techniques like deep learning and gradient boosting to your company's rows and columns.
Inside Advanced Analytics for Business you'll learn how to:
Pick the right machine learning approach for your data
Apply deep learning to tabular data
Deploy tabular machine learning locally and in the cloud
Pipelines to automatically train and maintain a model
This book collects best practices, hard-won tips and tricks, and hands-on techniques for making sense of tabular data using advanced machine learning techniques. Inside, you'll discover how to use XGBoost and LightGBM on tabular data, optimize deep learning libraries like TensorFlow and PyTorch for tabular data, and use cloud tools like Vertex AI to create an automated MLOps pipeline.
Mark Ryan is a technical writing manager at Google. He studied computer science at the University of Waterloo and at the University of Toronto. In addition to a keen interest in deep learning with tabular data, Mark is interested in applications of large language models. Luca Massaron is a data scientist with more than a decade of experience in transforming data into smarter artifacts, solving real-world problems, and generating value for businesses and stakeholders. He is the author of bestselling books on AI, machine learning, and algorithms.
| Erscheinungsdatum | 11.03.2025 |
|---|---|
| Zusatzinfo | Illustrations |
| Verlagsort | New York |
| Sprache | englisch |
| Maße | 186 x 234 mm |
| Gewicht | 910 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
| ISBN-10 | 1-63343-854-6 / 1633438546 |
| ISBN-13 | 978-1-63343-854-5 / 9781633438545 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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