Statistical Foundations of Machine Learning

This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data.

**Tag(s):**
Big Data
Machine Learning
Statistics

**Publication date**: 01 Jan 2016

**ISBN-10**:
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**ISBN-13**:
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**Paperback**:
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**Views**: 3,094

Statistical Foundations of Machine Learning

This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data.

From the Book Description:

We are in the era of big data. The procedure for finding useful patterns in data is known by different names in different communities but more and more, it is grouped under the label of machine learning. This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. This manuscript aims to find a good balance between theory and practice by situating most of the theoretical notions in a real context with the help of practical examples and real datasets. All the examples are implemented in the statistical programming language R.

We are in the era of big data. The procedure for finding useful patterns in data is known by different names in different communities but more and more, it is grouped under the label of machine learning. This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. This manuscript aims to find a good balance between theory and practice by situating most of the theoretical notions in a real context with the help of practical examples and real datasets. All the examples are implemented in the statistical programming language R.

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About The Author(s)

Dr. Souhaib Ben Taieb is a Lecturer in Business Analytics and Data Science at Monash University in Melbourne, Australia. He received an M.Sc and a Ph.D. in Computer Science (Machine learning) from the Free University of Brussels in Belgium. His main research interests include machine learning, large scale time series modeling and forecasting, and smart grid analytics.

Gianluca Bontempi is a Professor at Département d'Informatique, at Université Libre de Bruxelles. He graduated with honors in Electronic Engineering (Politecnico of Milan, Italy) and obtained his PhD in Applied Sciences (ULB, Brussels, Belgium). His interests cover data mining, machine learning, bioinformatics, time series prediction and simulation.

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