Data science for business

By Foster J. Provost, Tom Fawcett. 2013

327 citations recorded by the source corpus.

How researchers see this paper

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Data science and prediction (2013, background): “30 Skills Machine learning skills are fast becoming necessary for data scientists as companies navigate the data deluge and try to build automated decision systems that hinge on predictive accuracy.(25) A basic course in machine learning is necessary in today’s marketplace.”
Deep Reinforcement Learning: An Overview (2017, background): “2 MORE BOOKS • theoretical RL books (Bertsekas, 2012; Bertsekas and Tsitsiklis, 1996; Szepesvári, 2010) • an operations research oriented RL book (Powell, 2011) • an edited RL book (Wiering and van Otterlo, 2012) • Markov decision processes (Puterman, 2005) • deep learning (Deng and Dong, 2014) • ma”
Deep Reinforcement Learning (2018, background): “tions research and management (Powell, 2011), and is also related to psychology and neuroscience (Sutton and Barto,2018). Machine learning is the basis for big data, data science (Blei and Smyth,2017;Provost and Fawcett, 2013), predictive modeling (Kuhn and Johnson,2013), data mining (Han et al.,201”