Looking at Data Science through the Lens of Scheduling and Load Balancing

Author:

Eugênio da Silveira Diórgenes,Souza dos Reis Eduardo,Simon Bavaresco Rodrigo,Miguel Gomes Marcio,André da Costa Cristiano,Luis Victoria Barbosa Jorge,Stoffel Antunes Rodolfo,Machado Júnior Alvaro,Saad Rodrigo,da Rosa Righi Rodrigo

Publisher

IntechOpen

Reference16 articles.

1. Amirian P, van Loggerenberg F, Lang T. Data Science and Analytics. Cham: Springer International Publishing; 2017. pp. 15-37

2. Gibert K, Horsburgh JS, Athanasiadis IN, Holmes G. Environmental data science. Environmental Modelling and Software. 2018;106:4-12. Special Issue on Environmental Data Science. Applications to Air quality and Water cycle

3. Grus J. Data Science from Scratch: First Principles with Python. 1st ed. O’Reilly Media, Inc.; 2015. Available from: https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X

4. Ahmad A, Paul A, Din S, Rathore MM, Choi GS, Jeon G. Multilevel data processing using parallel algorithms for analyzing big data in high-performance computing. International Journal of Parallel Programming. 2018;46(3):508-527

5. Bomatpalli T, Wagh R, Balaji S. High performance computing and big data analytics paradigms and challenges. International Journal of Computer Applications. 2015;116(04):28-33

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