The Cloud
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Computation and Storage in the Cloud
Computation and Storage in the Cloud is the first comprehensive and systematic work investigating the issue of computation and storage trade-off in the cloud in order to reduce the overall application cost. Scientific applications are usually computation and data intensive, where complex computation tasks take a long time for execution and the generated datasets are often terabytes or petabytes in size. Storing valuable generated application datasets can save their regeneration cost when they are reused, not to mention the waiting time caused by regeneration. However, the large size of the scientific datasets is a big challenge for their storage. By proposing innovative concepts, theorems and algorithms, this book will help bring the cost down dramatically for both cloud users and service providers to run computation and data intensive scientific applications in the cloud. - Covers cost models and benchmarking that explain the necessary tradeoffs for both cloud providers and users - Describes several novel strategies for storing application datasets in the cloud - Includes real-world case studies of scientific research applications - Covers cost models and benchmarking that explain the necessary tradeoffs for both cloud providers and users - Describes several novel strategies for storing application datasets in the cloud - Includes real-world case studies of scientific research applications
Introduction to Machine Learning in the Cloud with Python
This book provides an introduction to machine learning and cloud computing, both from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.