Online Machine Learning

A Practical Guide with Examples in Python
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Éditeur :

Springer

Paru le : 2024-02-05

This book deals with the exciting, seminal topic of Online Machine Learning (OML). The content is divided into three parts: the first part looks in detail at the theoretical foundations of OML, comparing it to Batch Machine Learning (BML) and discussing what criteria should be developed for a meani...
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Éditeur

Collection
n.c

Parution
2024-02-05

Pages
155 pages

EAN papier
9789819970063

Auteur(s) du livre


Prof. Dr. Thomas Bartz-Beielstein is an artificial intelligence expert with 30+ years of experience. He is a professor of applied mathematics at TH Köln in Germany and the director of the Institute for Data Science, Engineering, and Analytics (IDE+A). His research lies in artificial intelligence, machine learning, simulation, and optimization. He developed the Sequential Parameter Optimization (SPO). SPO integrates approaches from surrogate model-based optimization and evolutionary computing. He has worked on diverse topics from applied mathematics and statistics, design of experiments, simulation-based optimization and applications in domains as water industry, elevator control, or mechanical engineering.?Eva Bartz is an expert in law and data protection. Within the wide area of data protection, she specializes particularly in the application of artificial intelligence and its benefits and dangers. Based on this vast experience,she founded Bartz & Bartz GmbH in 2014 together with Thomas Bartz-Beielstein and offers consulting for a variety of customers. She translates the academic expertise of Bartz & Bartz GmbH’s advisors - who are leading experts in their fields - into a benefit for her customers. One of these customers was the Federal Statistical Office of Germany (Destatis), and the study for them laid the groundwork for this book. 

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EAN PDF
9789819970070
Prix
63,29 €
Nombre pages copiables
1
Nombre pages imprimables
15
Taille du fichier
6943 Ko
EAN EPUB
9789819970070
Prix
63,29 €
Nombre pages copiables
1
Nombre pages imprimables
15
Taille du fichier
15882 Ko

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