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 meaningful comparison. The second part provides practical considerations, and the third part substantiates them with concrete practical applications.

The book is equally suitable as a reference manual for experts dealing with OML, as a textbook for beginners who want to deal with OML, and as a scientific publication for scientists dealing with OML since it reflects the latest state of research. But it can also serve as quasi OML consulting since decision-makers and practitioners can use the explanations to tailor OML to their needs and use it for their application and ask whether the benefits of OML might outweigh the costs.

OML will soon become practical; it is worthwhile to get involved with it now. This book already presents some tools that will facilitate the practice of OML in the future. A promising breakthrough is expected because practice shows that due to the large amounts of data that accumulate, the previous BML is no longer sufficient. OML is the solution to evaluate and process data streams in real-time and deliver results that are relevant for practice.

�ber die Autorin bzw. den Autor

Prof. Dr. Thomas Bartz-Beielstein is an artificial intelligence expert with 30+ years of experience. He is a professor of applied mathematics at TH K�ln 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.

��ber diesen Titel� kann sich auf eine andere Ausgabe dieses Titels beziehen.

Anbieterinformationen

GreatBookPrices.com is your top source for finding new books at the absolute lowest prices, guaranteed ! We offer big discounts - everyday - on millions of titles in virtually any category, from Architecture to Zoology -- and everything in between. Discover great deals and super-savings, on professional books, text book titles, the newest computer guides, or your favorite fiction authors. You'll find it all - at HUGE SAVINGS - at GreatBookPrices. Browse through our complete online product catalog today. Serving customers around the world for years, we help thousands find just the books they're looking for -- at incredibly low, bargain prices.

Zur Homepage des Verk�ufers

Unternehmensdaten des Verk�ufers

Far Corner Europe Limited
19-20 Bourne Court, 19-20 Bourne Court, Woodford Green, IG8 8HD, United Kingdom

Gesch�ftsbedingungen und Versandinformationen

Verkaufsbedingungen

Company Name: GreatBookPricesUK
Legal Entity: Far Corner Europe Limited
Address: 19-20 Bourne Court, Southend Road, Woodford Green Essex, UK IG8 8HD
Registration #: 10691061
Authorized representative: Danielle Hainsey

Versandbedingungen

Our warehouses across the globe are fully operational without substantial delays. We are working hard and continue to overcome the daily challenges presented by COVID-19. There have been reports that delivery carriers are experiencing large delays resulting in longer than normal deliveries to customers. We would like to apologize in advance if your item arrives later than the expected delivery due date

Internal processing of your order will take about 1-2 business days. Please allow an additional 10-20 business days for Royal Mail delivery.

Impressum & Info zum Verk�ufer