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  Natural language processing recipes: unlocking text data with machine learning and deep learning using Python
Kulkarni A., Shivananda A.,  Apress, New York, NY, 2019. 260 pp. Type: Book (978-1-484242-66-7)

Python--30 years in the making and named after the hilariously funny Monty Python’s Flying Circus--has become the preferred language for natural language processing (NLP) for a number of reasons: it is easier to program than...

Nov 26 2021  
   My robot gets me: how social design can make new products more human
Diana C.,  Harvard Business Review Press, Boston, MA, 2021. 304 pp. Type: Book (978-1-633694-42-2)

The subtitle--how social design can make new products more human--is accurate. Most running exemplars are robots, but Alexa and the Roomba robot vacuum and others also show up. We are living in a time when technology can support a...

Nov 23 2021  
  Mining imperfect data: with examples in R and Python (2nd ed.)
Pearson R.,  SIAM, Philadelphia, PA, 2020. 184 pp. Type: Book (978-1-611976-26-7)

Data analysis--including both data mining and machine learning--has made a lot of progress in the past decade. Both the R and Python programming languages have been used to analyze data. The Achilles’ heel in this task is the handl...

Nov 19 2021  
  Environmental audio scene and sound event recognition for autonomous surveillance: a survey and comparative studies
Chandrakala S., Jayalakshmi S.  ACM Computing Surveys 52(3): 1-34, 2019. Type: Article

As my colleagues and I define in a previous paper, “environmental sound recognition (AESR) is a relatively new discipline of computer science destined to extend the field of speech-based applications, or the study of music sounds, by explori...

Nov 11 2021  
   Practical natural language processing with Python: with case studies from industries using text data at scale
Sri M.,  Apress, New York, NY, 2021. 272 pp. Type: Book (978-1-484262-45-0)

Understanding spoken and written communication can be difficult, even for humans. Creating linguistic processes and algorithms for computers is extremely challenging. Natural language processing (NLP) technology is more common than most people rea...

Nov 9 2021  
  Learning scientific programming with Python (2nd ed.)
Hill C.,  Cambridge University Press, Cambridge, UK, 2020. 570 pp. Type: Book (978-1-108745-91-8)

The author is a scientist, and this text is for science and engineering students who want to learn Python. It covers Python well using many science-based examples. While the book does not explain the science, it does include the appropriate formul...

Nov 2 2021  
  Quantum machine learning with Python: using Cirq from Google Research and IBM Qiskit
Pattanayak S.,  Apress, New York, NY, 2021. 384 pp. Type: Book (978-1-484265-21-5)

Machine learning has proved to be very successful in computer science, with applications to many areas in human life. Quantum computing is a marvelous new computation model with applications to some very hard problems. This book is at the crossroa...

Oct 28 2021  
  Interpolatory methods for model reduction
Antoulas A., Beattie C., Güğercin S.,  SIAM, Philadelphia, PA, 2020. 232 pp. Type: Book (978-1-611976-07-6)

Interpolation methods are automatic techniques for reducing the size and other complexities of large complicated models. Modeling physical systems using differential equations and geometrical properties has been popular among scientists and engine...

Oct 26 2021  
  Data-driven anomaly detection with timing features for embedded systems
Lu S., Lysecky R.  ACM Transactions on Design Automation of Electronic Systems 24(3): 1-27, 2019. Type: Article

The Internet of Things (IoT) continues to usher in the joys of connecting several house appliances and electronic devices via wired and wireless networks. But how should the rooted systems that support IoT provide security and privacy for online u...

Oct 20 2021  
  Foundations of probabilistic programming
Barthe G., Katoen J., Silva A.,  Cambridge University Press, Cambridge, UK, 2021. 582 pp. Type: Book (978-1-108488-51-8)

This book covers various programming languages for probabilistic programming. The languages are described using syntax, semantics, and examples. It also looks at the theories related to the semantics of probability constructs and discusses the rea...

Oct 18 2021  
 
 
 
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