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Reviewers have found these items notable and have self-selected them for review.
  1-10 of 6809 results Date Reviewed  
  Advanced machine learning with Python
Hearty J.,  Packt Publishing, Birmingham, UK, 2016. 278 pp. Type: Book (978-1-784398-63-7)

Machine learning and deep learning are two research areas that have created excitement and interest in many application domains. By using Python as the implementation medium, and by releasing most of the initial example set as an accompanying reso...

Sep 22 2017  
  A survey on malware detection using data mining techniques
Ye Y., Li T., Adjeroh D., Iyengar S.  ACM Computing Surveys 50(3): 1-40, 2017. Type: Article

It is not new that software is eating the world [1]. Industries and businesses everywhere are being “softwareized.” Meanwhile, we cannot deny that malware (malicious software) is also having a feast. This paper provides a comprehensive...

Sep 22 2017  
  Migrating large-scale services to the cloud
Passmore E.,  Apress, New York, NY, 2016. 122 pp. Type: Book (978-1-484218-72-3)

Are you moving large-scale workloads that cannot scale well to Microsoft Azure? Then you might want to take a look at this book, which discusses lessons learned from large-scale migration to the public cloud (Azure)....

Sep 18 2017  
  Software reading techniques: twenty techniques for more effective software review and inspection
Zhu Y.,  Apress, New York, NY, 2016. 126 pp. Type: Book (978-1-484223-45-1)

Software professionals are trained to create software artifacts of all kinds. Surprisingly, they are not taught how to read and analyze the resulting requirements, designs, test cases, and code. Yang-Ming Zhu’s short book intends to address ...

Sep 14 2017  
   Speed, data, and ecosystems: excelling in a software-driven world
Bosch J.,  CRC Press, Inc., Boca Raton, FL, 2016. 343 pp. Type: Book (978-1-138198-18-0)

This book is a masterful exposition of how to develop large software programs, aimed at business leaders but useful to others. “Speed” refers to shortening the time required to get new software to the customer. “Data” refer...

Sep 14 2017  
  Cognitive (Internet of) Things: collaboration to optimize action
Sathi A.,  Palgrave Macmillan, New York, NY, 2016. 178 pp. Type: Book (978-1-137594-65-5)

Cognitive (Internet of) Things brings us a comprehensive view of the field, despite its small size (less than 180 pages). The book is well organized, with topics ranging from the basics of the subject to cognitive devices that function as h...

Sep 13 2017  
  C# 6 for programmers (6th ed.)
Deitel P., Deitel H.,  Prentice Hall Press, Upper Saddle River, NJ, 2016. 768 pp. Type: Book (978-0-134596-32-7)

The popularity of computer programming courses and their associated languages has led to the publication of numerous texts and reference books. Throughout the long history of computer programming books, there has been a standardized format: start ...

Sep 11 2017  
  Algorithms and models for network data and link analysis
Fouss F., Saerens M., Shimbo M.,  Cambridge University Press, New York, NY, 2016. 543 pp. Type: Book (978-1-107125-77-3)

A recent article in The Economist noted that data is to the twenty-first century what oil was to the twentieth century. Data is almost ubiquitously generated by humans as part of their everyday interactions on social networks, power grids, ...

Sep 8 2017  
  Fog computing for the Internet of Things: security and privacy issues
Alrawais A., Alhothaily A., Hu C., Cheng X.  IEEE Internet Computing 21(2): 34-42, 2017. Type: Article

Connecting everything to the Internet is attractive because it can bring efficiency and convenience in many areas. However, security and privacy issues can also occur. The problem is that it is difficult to apply existing security and privacy solu...

Sep 7 2017  
  Becoming agile: a grounded theory of agile transitions in practice
Hoda R., Noble J.  ICSE 2017 (Proceedings of the 39th International Conference on Software Engineering, Buenos Aires, Argentina,  May 20-28, 2017) 141-151, 2017. Type: Proceedings

The delusion of agility is as common among practicing software engineering teams as is the common cold during the fall season. A software development life cycle (SDLC) as sophisticated as agile can thrive if a team can express a sufficient maturit...

Sep 7 2017  
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