Reading materials

In addition to the lectures and handouts (distributed after each lecture), you will find relevant topics discussed in great details in the following materials.

• [video] Ryan Berry, Matthew Puckett, and Laura Edell. A Brief History of Machine Learning. 2018
• [book] Christopher Bishop. Pattern Recognition and Machine Learning. 2006
• [book] Andreas Müller and Sarah Guido. Introduction to Machine Learning with Python. 2017.
• [book] Sebastian Raschka. Python Machine Learning. 2015.
• [book] Michael Nielsen. Neural Networks and Deep Learning. Dec. 2019
• [book] Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Deep Learning. 2015

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