Bibliography for Machine Learning (CMP9137M) BETA

Alpaydin E, Introduction to Machine Learning, vol Adaptive computation and machine learning (Third edition, The MIT Press 2014)

Bishop, C. M., Pattern Recognition and Machine Learning, vol Information science and statistics (Springer 2006)

Chollet F, Deep Learning with Python (Manning 2018)

‘Deep Learning’ <http://www.deeplearningbook.org/>

Goodfellow I, Bengio Y and Courville A, Deep Learning, vol Adaptive computation and machine learning (The MIT Press 2016) <https://ebookcentral-proquest-com.proxy.library.lincoln.ac.uk/lib/ulinc/detail.action?docID=6287197>

‘IEEE Transactions on Neural Networks and Learning Systems’ <http://ieeexplore.ieee.org.proxy.library.lincoln.ac.uk/xpl/RecentIssue.jsp?punumber=5962385>

‘IEEE Transactions on Pattern Analysis and Machine Intelligenc’ <http://ieeexplore.ieee.org.proxy.library.lincoln.ac.uk/xpl/RecentIssue.jsp?punumber=34>

Marsland S, Machine Learning: An Algorithmic Perspective, vol Chapman&Hall/CRC machine learning&pattern recognition series (Second edition, Chapman & Hall/CRC 2014)

Mitchell, Tom M., Machine Learning, vol McGraw-Hill series in computer science (International ed, McGraw-Hill 1997)

Rogers S and Girolami M, A First Course in Machine Learning (Second edition, CRC Press 2017) <https://www.vlebooks.com/vleweb/product/openreader?id=UniLincoln&isbn=9781315382159>

Shukla N and Fricklas K, Machine Learning with TensorFlow (Manning Publications 2018)

Sutton, Richard S. and Barto, Andrew G., Reinforcement Learning: An Introduction, vol Adaptive computation and machine learning (MIT Press 1998)

Taylor K, Deep Learning Using MATLAB: Neural Network Applications ([Createspace Independent Publishing Platform] 2017)

‘The Journal of Machine Learning Research (JMLR)’ <https://go.openathens.net/redirector/lincoln.ac.uk?url=https%3A%2F%2Fdl.acm.org%2Fjournal%2Fjmlr>