Abstract
Machine learning, data analysis, and artificial intelligence are becoming increasingly ubiquitous in our lives, and more central to the high-tech industry. These fields play a central role in many of the recent and upcoming revolutions in computing; for example, social networks, streaming video on demand, personal assistants (e.g., Alexa, Siri, and Google Assistant), and self-driving cars. Alphabet’s Executive Chairman, Eric Schmidt, went a step further at the 2016 Google Cloud Computing Conference in San Francisco when he said, “Machine learning and crowdsourcing data will be the basis and fundamentals of every successful huge IPO win in five years.”
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G. Strang. Introduction to Linear Algebra. Wellesley Cambridge Press, fourth edition, 2009.
W. Rudin. Principles of Mathematical Analysis. McGraw-Hill, third edition, 1976.
W. F. Trench. Introduction to Real Analysis. Pearson, 2003.
G. Thomas, M. D. Weir, and J. Hass. Thomas’ Calculus. Addison Wesley, twelfth edition, 2009.
W. Feller. An Introduction to Probability Theory and its Application, volume 1. John Wiley and Sons, third edition, 1968.
Sheldon M. Ross. Introduction to Probability Models. Academic Press, tenth edition, 2009.
A. DasGupta. Fundamentals of Probability: A First Course. Springer, 2010.
G. Casella and R. L. Berger. Statistical Inference. Duxbury, second edition, 2001.
G. A. Seber and A. J. Lee. Linear Regression Analysis. Wiley Interscience, 2003.
M. Kutner, C. Nachtsheim, J. Neter, and W. Li. Applied Linear Statistical Models. McGraw-Hill, fifth edition, 2004.
B. Schölkopf and A. Smola. Learning with Kernels. MIT Press, 2002.
C. D. Manning and H. Schutze. Foundations of Statistical Natural Language Processing. MIT Press, 1999.
C. M. Bishop. Pattern Recognition and Machine Learning. Springer, 2006.
K. P. Murphy. Machine Learning: A Probabilistic Perspective. MIT Press, 2012.
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Lebanon, G., El-Geish, M. (2018). Introduction: How to Use This Book?. In: Computing with Data. Springer, Cham. https://doi.org/10.1007/978-3-319-98149-9_1
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DOI: https://doi.org/10.1007/978-3-319-98149-9_1
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