This book is what it says it is on the cover: namely a practical introduction to the legal issues surrounding Cloud computing. The author confirms in the Foreword that it is written for both lawyers and non lawyers alike with little background knowledge of the subject. The book covers all ...
The impact of cloud computing on industry and end users would be difficult to overstate: many aspects of everyday life have been transformed by the omnipresence of software that runs on cloud networks. By leveraging cloud computing, startups and businesses are able to optimize costs and increase...
Cloud Computing: A Practical Approachprovides a comprehensive look at the emerging paradigm of Internet-based enterprise applications and services. This accessible book offers a broad introduction to cloud computing, reviews a wide variety of currently available solutions, and discusses the cost savings ...
数据结构与算法分析 : A practical introduction to data structures and algorithm analysis : C++版 本书是数据结构和算法分析方面的经典教材, 通过C程序的实现, 着重阐述了抽象数据类型 (ADT ) 的概念, 并对算法的效率、性能和运行时间进行了分析。 谢弗张铭,刘晓丹 - 数据结构与算法分析 : A practical introduc...
So there are obvious cost and practical advantages: you don't have to worry about expensive software licenses or security updates, and your staff can simply and securely share documents across business locations (and work on them just as easily from home). Using cloud computing to run ...
Those seeking a concise, accessible introduction to the topic which quickly enables them to build practical systems or conduct further research will find this essential reading. 展开 DOI: 10.1561/3300000019 年份: 2018 收藏 引用 批量引用 报错 分享 ...
The key metric for your business is the amount of time needed to complete a project from data ingestion to deployment. In practical terms, this means that your machine learning software should integrate with popular Hadoop and cloud formats, and it should export predictive models as code that ...
The key metric for your business is the amount of time needed to complete a project from data ingestion to deployment. In practical terms, this means that your machine learning software should integrate with popular Hadoop and cloud formats, and it should export predictive models as code that ...