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Julia for Data Science, by Zacharias Voulgaris PhD
Free Ebook Julia for Data Science, by Zacharias Voulgaris PhD
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Master how to use the Julia language to solve business critical data science challenges. After covering the importance of Julia to the data science community and several essential data science principles, we start with the basics including how to install Julia and its powerful libraries. Many examples are provided as we illustrate how to leverage each Julia command, dataset, and function.
Specialized script packages are introduced and described. Hands-on problems representative of those commonly encountered throughout the data science pipeline are provided, and we guide you in the use of Julia in solving them using published datasets. Many of these scenarios make use of existing packages and built-in functions, as we cover:
- Sales Rank: #128440 in Books
- Published on: 2016-09-01
- Original language: English
- Dimensions: 9.25" h x .83" w x 7.50" l, .0 pounds
- Binding: Paperback
- 415 pages
About the Author
Dr. Zacharias Voulgaris was born in Athens, Greece. He studied Production Engineering and Management at the Technical University of Crete, shifted to Computer Science through a Masters in Information Systems & Technology (City University of London), and then to Data Science through a PhD on Machine Learning (University of London). He has worked at Georgia Tech as a Research Fellow, at an e-marketing startup in Cyprus as an SEO manager, and as a Data Scientist in both Elavon (GA) and G2 (WA). He also was a Program Manager at Microsoft, on a data analytics pipeline for Bing. Zacharias has authored two books and several scientific articles. His first book, Data Scientist - The Definitive Guide to Becoming a Data Scientist (Technics Publications), has been translated into Korean and Chinese. He has also reviewed a number of data science books (mainly on Python and lately on R) and had developed a number of new metrics and functions for data analytics. Apart from data science, he also has a passion for new technologies, literature, and music.
Most helpful customer reviews
0 of 0 people found the following review helpful.
It has been impossible to date to find an errata ...
By Amazon Customer
It has been impossible to date to find an errata list for this book. The book appears to need one. Otherwise, kind of OK.
2 of 3 people found the following review helpful.
Reasonable but mixed
By Johan V Silen
The book is a bit mixed introducing data science concepts with examples using the excellent new Julia language which definitely will be the future.
6 of 6 people found the following review helpful.
Great book for Data Scientists looking into Julia
By Alberto
I loved this book: it explains exactly what the title says: Julia for Data Science! The first few chapters are the 101 of Julia, but then the book turns and goes deeper and deeper into Data Science.
As I longtime Python developer, I appreciated the conciseness and the speed of Julia and the variety of libraries available for Data Science. I already approached Julia in the past, but I found other books too much CS-oriented or too general purpose: with the main focus on Data Science this one is different, allowing me to move my first steps and becoming proficient in Julia in weeks. A few chapters into the book, and I was already ready to experiment on my own, effectively changing and shaping the code to test Julia on my professional projects.
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