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  1-10 of 6896 Reviews with General Term: Languages Date Reviewed
  DevOps in Python: infrastructure as Python
Zadka M.,  Apress, New York, NY, 2019. 188 pp. Type: Book (978-1-484244-32-6)

DevOps is a hot topic in software engineering these days, and Python is one of the most popular programming languages in the world. What could be better than a pithy book combining the two? Well, that is exactly what Moshe Zadka, a long-time op...

Dec 23 2021
  Competitive programming in Python: 128 algorithms to develop your coding skills
Dürr C., Vie J.,  Cambridge University Press, Cambridge, UK, 2021. 264 pp. Type: Book (978-1-108716-82-6)

Programming contests typically ask teams of programmers to develop solutions to several posed problems in a limited amount of time. Knowledge of algorithms and the techniques for implementing those algorithms efficiently are critical for success, ...

Dec 9 2021
   Programming for computations - Python (2nd ed.)
Linge S., Langtangen H.,  Springer International Publishing, New York, NY, 2020. 232 pp. Type: Book (978-3-319324-27-2)

True story: many years ago, while studying applied mathematics, a young man took a one credit hour course in programming. This consisted of an introduction to FORTRAN II and a single assignment: write a program to triangularize a matrix. Now, havi...

Dec 7 2021
   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
  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
   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
  A survey of machine learning for big code and naturalness
Allamanis M., Barr E., Devanbu P., Sutton C.  ACM Computing Surveys 51(4): 1-37, 2018. Type: Article

There is a rising demand for effective software tools that can help developers build reliable and maintainable software systems. There has been abundant research to help developers track bugs and verify program properties and refactor code. Recent...

Nov 4 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
  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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