Kaminski / Szufel Julia 1.0 Programming Cookbook

Over 100 numerical and distributed computing recipes for your daily data science workflow
1. Auflage 2018
ISBN: 978-1-78899-882-6
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 460 Seiten

No detailed description available for "Julia 1.0 Programming Cookbook".

Autoren/Hrsg.

Kaminski, Bogumil

Szufel, Przemyslaw

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen

Inhaltsverzeichnis

Table of Contents - Installing and Setting up Julia
- Data Structures and Algorithms
- Data Engineering in Julia
- Numerical Computing with Julia
- Variables, types and functions
- Metaprogramming and advanced typing
- Handling analytical data
- Julia Workflow
- Data Science
- Distributed Computing

Über Autor(innen)

Kaminski Bogumil:
Bogumi Kamiski (GitHub username: bkamins) is an associate professor and head of the Decision Support and Analysis Unit at the SGH Warsaw School of Economics, as well as adjunct professor at the data science laboratory, Ryerson University, Toronto. He is coeditor of the Central European Journal of Economic Modeling and Econometrics, and of the Multiple Criteria Decision Making journal. His scientific interests center on operational research and computational social science. He has authored over 50 research articles on simulation, optimization, and prediction methods. He also has 15+ years' experience in the deployment of large-scale advanced analytics solutions for industry and public administration.Szufel Przemyslaw:
Przemysaw Szufel (GitHub username: pszufe) is an assistant professor in the Decision Support and Analysis Unit at the SGH Warsaw School of Economics. His current research focuses on distributed systems and methods for the execution of large-scale simulations for numerical experiments and optimization. He is working on asynchronous algorithms for the parallel execution of large-scale computations in the cloud and distributed computational environments. He has authored, and co-authored, several open source tools for high-performance and numerical simulation.