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This book is initially my learning note for machine learning. Later on I decided to re-organize it into a free e-book so that many of you may benefit from it. Note that I will try to contact professors and experts to help me keep this right, clear and easy to understand, there may still be something wrong, unclear and difficult to read (such as its formulas, tables etc.). In that case, to help me better organize the problems and learn from you, please file a issue here.
Author: Xiaozhe Yao
Some of the content comes from the following courses:
- Reliable and Interpretable Artificial Intelligence at ETH Zurich by Prof. Dr. Martin Vechev.
- Linear Algebra by Prof. Dr. Stefan Sauter & Analysis by Prof. Dr. Rémi Abgrall at the University of Zurich.
- Pattern Recognition at Shenzhen University by Prof. Dr. Shiqi Yu.
- Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares by Stephen Boyd and Lieven Vandenberghe
- Deep Learning by Yoshua Bengio
- Deep Learning-500-Questions
There are many other different resources (websites, papers, softwares) that contribute to the contents, and I will try to cite them individually when it is mentioned. But sometimes, I may forget to. In that case, Please contact me and I will fix it as soon as possible.
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