This book is based in part on my earlier work. Pattern Recognition: Applications to Large Data-Set Problems, published by Marcel Dekker_: Inc. in 1984. It was originally intended that this volume be a second editon of that work. However, due to the tremendous amount of material added it seemed that a new title. Pattern Recognition...

• Adopt microservices-based architecture and deploy it at scale
• Build your complete microservice architecture using different recipes for different solutions
• Identify specific tools for specific scenarios and deliver immediate business results, correlate use cases, and adopt them...

Knowledge-Based Clustering demonstrates how to design navigational platforms that enable information seekers to make sense of and better exploit highly diverse and heterogeneous sets of data. Moving beyond fuzzy clustering, the author shows how the promising new paradigm of...

Now, IBM offers complete, start-to-finish...

This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by...

Plan, design, and implement highly available Windows solutions using the expert advice in this detailed guide. Written by a network infrastructure design specialist, this book covers the planning, development, cost analysis, management, installation, configuration, and roll out of several clustering and load balancing technologies....

R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages.  With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of...