Malcolm Sherrington - Mastering Julia

Malcolm Sherrington has been working in computing for over 35 years. He holds degrees in mathematics, chemistry, and engineering and has given lectures at two different universities in the UK as well as worked in the aerospace and healthcare industries. Currently, he is running his own company in the finance sector, with specific interests in High Performance Computing and applications of GPUs and parallelism.

Always hands-on, Malcolm started programming scientific problems in Fortran and C, progressing through Ada and Common Lisp, and recently became involved with data processing and analytics in Perl, Python, and R.

Malcolm is the organizer of the London Julia User Group. In addition, he is a co-organizer of the UK High Performance Computing and the financial engineers and Quant London meetup groups.

I would like to dedicate this book to the memory of my late wife, Hazel Sherrington, without whose encouragement and support, my involvement in Julia would not have started but who is no longer here to see the culmination of her vision.

Also, I wish to give special thanks to Barbara Dor and James Weymes for their substantive help and material assistance in the preparation of this book.

Gururaghav Gopal is presently working as a risk management consultant in a start-up. Previously, he worked at Paterson Securities as an quant developer/trader consultant .He has also worked as a data science consultant and was associated with an e-commerce organization. He has been teaching graduate and post-graduate students of VIT University, Vellore, in the areas of pattern recognition, machine learning, and big data. He has been associated with several research organizations, namely IFMR and NAL, as a research associate. He has also reviewed Learning Data Mining with R , Packt Publishing and has been a reviewer for a few journals and conferences.

He did his bachelor's degree in electrical and electronics engineering with a master's degree in computer science and engineering. He later did his course work from IFMR in financial engineering and risk management, and since then, he has been associated with the financial industry. He has won many awards and has a few international publications to his credit.

He is interested in programming, teaching, and doing consulting work. During his free time, he listens to music.

He can be contacted for professional consulting through LinkedIn at in.linkedin.com/in/gururaghavg.

Zhuo QL (a.k.a KDr2 online) is a free developer from China who has about 10 years' experience in Linux, C, C++, Java, Python, and Perl development. He loves to participate in and contribute to the open source community (which, of course, includes the Julia community). He maintains a personal website at http://kdr2.com; you can find out more about him there.

Dan Wlasiuk is the author of various Julia packages including TimeSeries and Quandl, and he is also the founder of the JuliaQuant GitHub organization of quantitative finance related packages.

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Preface

Julia is a relatively young programming language. The initial design work on the Julia project began at MIT in August 2009, and by February 2012, it became open source. It is largely the work of three developers Stefan Karpinski, Jeff Bezanson, and Viral Shah. These three, together with Alan Edelman, still remain actively committed to Julia and MIT currently hosts a variety of courses in Julia, many of which are available over the Internet.

Initially, Julia was envisaged by the designers as a scientific language sufficiently rapid to make the necessity of modeling in an interactive language and subsequently having to redevelop in a compiled language, such as C or Fortran. At that time the major scientific languages were propriety ones such as MATLAB and Mathematica, and were relatively slow. There were clones of these languages in the open source domain, such as GNU Octave and Scilab, but these were even slower. When it launched, the community saw Julia as a replacement for MATLAB, but this is not exactly case. Although the syntax of Julia is similar to MATLAB, so much so that anyone competent in MATLAB can easily learn Julia, it was not designed as a clone. It is a more feature-rich language with many significant differences that will be discussed in depth later.