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Eugene Callahan
New York University
Brooklyn, New York
 

Dr. Eugene Callahan has been involved in computing for over three decades, as both a software engineer and teacher (currently at the New York University Tandon School of Engineering). As a developer, he has worked on personal finance software (Managing Your Money), options trading systems, healthcare applications, and the development of new computer languages. He has taught undergraduate courses in discrete mathematics, statistics, algorithms, operating systems, object-oriented programming, and software engineering. In his role as a teacher, he created Tandon’s first DevOps course.

Eugene also founded Koukou Data, a data aggregation company that seeks to automate the process of retrieving time series data and organizing it so as to meet the requirements of an end user. Koukou Data’s core technology is an application programming interface (API) server that handles requests to fetch and merge a variety of data types from across the Internet. Koukou Data’s software is currently used by a major trade association.

Eugene’s writing has appeared in Dr. Dobb’s Journal, Software Development, Computer Language, Java Developer’s Journal, Cutter IT Journal, Computing Reviews, Review of Political Economy, Journal of Social Economics, British Journal for the History of Philosophy, Critical Review, History: Reviews of New Books, American Journal of Economics and Sociology, Collingwood and British Idealism Studies, Ideas on Liberty, Modern Age, Christian Science Monitor, NYU Journal of Law & Liberty, and more. He is the author of the books Economics for real people and Oakeshott on Rome and America, and co-editor of the books Tradition versus rationalism, Critics of enlightenment rationalism, and Critics of enlightenment rationalism revisited.

Eugene holds a master’s degree from the London School of Economics and a PhD from Cardiff University in Wales. He has been a reviewer for Computing Reviews since 2017.


     

 Discovery of ill-known motifs in time series data
Deppe S., Springer International Publishing, Berlin, Germany, 2021. 220 pp.  Type: Book (978-3-662642-14-6)

Today, as we are drowning in data, we desperately need bits of dry land where we can climb out of the information ocean and gain useful perspectives. The book under review provides one such vantage point, and anyone whose work involves finding pat...

 

Python for probability, statistics, and machine learning (2nd ed.)
Unpingco J., Springer International Publishing, New York, NY, 2019. 384 pp.  Type: Book (978-3-030185-44-2)

The aim of this book is to offer programmers a tutorial on how to use Python libraries, like NumPy, Matplotlib, Pandas, SciPy, and SymPy, to perform probability evaluations and statistical analyses as the foundations for studying machi...

 

Devops in python: Infrastructure as Python
Zadka M., Apress, Berkeley, CA, 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...

 

Microservices and containers
Kocher P., Addison-Wesley Professional, Boston, MA, 2018. 304 pp.  Type: Book (978-0-134598-38-3)

Microservices and containers is an interesting book, albeit a flawed one. It addresses two important topics, but only loosely justifies putting the two topics in the same work. It is divided into three sections: the first addres...

 

Python unit test automation: practical techniques for Python developers and testers
Pajankar A., Apress, New York, NY, 2017. 111 pp.  Type: Book (978-1-484226-76-6)

Automated unit testing is a crucial part of the agile and DevOps approaches to software creation and deployment. The ability to get code into production with great regularity (companies good at this may deploy code into production hund...

 
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