Big Data (1 º Sem 2018/2019)

ECO , ECN , FIN , GES , MNG , MAEG , EAP (Econometria Aplicada e Previsão)

Bibliografia

Principal

• Andy Konwinski, Holden Karau, Matei Zaharia, and Patrick Wendell,, Learning Spark , 1st Ed. O?Reilly Media., 2015
• Bart Baesens, Analytics in a Big Data World: The Essential Guide to Data Science and its Applications, , , Wiley, 2014
• Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani., An Introduction to Statistical Learning with Applications in R, , 1st ed., Springer Texts in Statistics, 2013
• Ian Witten, Eibe Frank and Mark Hall. , Data Mining: Practical Machine Learning Tools and Techniques , 3rd ed., Morgan Kaufmann Publishers, 2011
• Trevor Hastie, Robert Tibshirani, Jerome Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2nd ed., Springer Texts in Statistics, 2009
• Tom White, Hadoop - The Definitive Guide, 4th Ed., O'Reilly Media, 2015

Secundária

• Jure Leskovek, Anand Rajamaran, Jeffrey David Ullman, Mining of Massive Datasets, 2nd ed., Cambridge University Press, 2014
• Simon Walkowiak, Big Data Analytics with R, Packt Publishing, 2016
• Mohammed Guller, Big Data Analytics with Spark: A Practitioner?s Guide to Using Spark for Large Scale Data Analysis, Apress, 2015