• Learning DevOps, container, and Kubernetes within one book.
• Leverage Kubernetes as a platform to deploy, scale, and run containers efficiently.
• A practical guide towards container management and...

Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mining with applications in bioinformatics. It supplies a broad, yet in-depth, overview of the application domains of data mining...

Since the publication of the bestselling first edition, many advances have been made in exploratory data analysis (EDA). Covering innovative approaches for dimensionality reduction, clustering, and visualization, Exploratory Data Analysis with MATLAB^®, Second Edition uses numerous examples and applications to...

Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely...

Collecting, analyzing, and extracting valuable information froma large amount of data requires easily accessible, robust,computational and analytical tools. Data Mining and BusinessAnalytics with R utilizes the open source software R for theanalysis, exploration, and simplification of large high-dimensionaldata sets. As a result, readers are...

The Radio Station is considered the standard work on radio media. It remains a concise and candid guide to the internal workings of radio stations and the radio industry in all of its various forms. Not only will you begin understand how each job at a radio station is best performed, you will learn how it meshes with those of...

Incorporating a new focus on data visualization and time series forecasting, Data Mining for Business Intelligence, Second Edition continues to supply insightful, detailed guidance on fundamental data mining techniques. This new edition guides readers through the use of the Microsoft Office Excel add-in XLMiner for developing...

• 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...

Open Source Computer Vision Library (OpenCV, http://opencv.org/) started as an Intel research initiative around 1999. Now, it is the most popular open source software library for computer vision and machine learning. In the beginning, it was a set of C library functions for image processing and computer vision. Now, it has C++, Python, Java,...