About the Reviewers
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, 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 on Machine Learning and as well as a couple of articles on AI topics. His first book, Data Scientist - The Definitive Guide to Becoming a Data Scientist (Technics Publications), has been translated into Korean and Chinese, while his latest one, Julia for Data Science (Technics Publications) is coming out this September. He has also reviewed a number of data science books (mainly on Python and R) and has a passion for new technologies, literature, and music.
I'd like to thank the people at Packt for inviting me to review this book and for promoting Data Science and particularly Julia through their books. Also, a big thanks to all the great authors out there who choose to publish their work through the lesser-known publishers, keeping the whole process of sharing knowledge a democratic endeavor.
Dipanjan Sarkar is a Data Scientist at Intel, the world's largest silicon company which is on a mission to make the world more connected and productive. He primarily works on analytics, business intelligence, application development and building large scale intelligent systems. He received his Master's degree in Information Technology from the International Institute of Information Technology, Bangalore. His area of specialization includes software engineering, data science, machine learning and text analytics.
Dipanjan's interests include learning about new technology, disruptive start-ups, data science and more recently deep learning. In his spare time he loves reading, writing, gaming and watching popular sitcoms. He has authored a book on Machine Learning titled R Machine Learning by Example, Packt Publishing and also acted as a technical reviewer for several books on Machine Learning and Data Science from Packt Publishing.
