Get Free Ebook Julia for Data ScienceBy Zacharias Voulgaris PhD

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Julia for Data ScienceBy 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:

An overview of the data science pipeline along with an example illustrating the key points, implemented in Julia

Options for Julia IDEs

Programming structures and functions

Engineering tasks, such as importing, cleaning, formatting and storing data, as well as performing data preprocessing

Data visualization and some simple yet powerful statistics for data exploration purposes

Dimensionality reduction and feature evaluation

Machine learning methods, ranging from unsupervised (different types of clustering) to supervised ones (decision trees, random forests, basic neural networks, regression trees, and Extreme Learning Machines)

Graph analysis including pinpointing the connections among the various entities and how they can be mined for useful insights.

Each chapter concludes with a series of questions and exercises to reinforce what you learned. The last chapter of the book will guide you in creating a data science application from scratch using Julia.

• Amazon Sales Rank: #583370 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.

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Julia for Data ScienceBy Zacharias Voulgaris PhD PDF