Difference between revisions of "Books"
From Research management course
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| − | = | + | =Machine learning for beginners= |
| − | + | * [https://arxiv.org/pdf/1709.02840 A Brief Introduction to Machine Learning for Engineers by Osvaldo Simeone, 2017-2018] | |
| + | * [https://www.semanticscholar.org/paper/Understanding-Machine-Learning%3A-From-Theory-to-Shalev-Shwartz-Ben-David/ce615ae61d67db8537e981a0a08da7f0f2ff1cee Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz, Shai Ben-David, 2014] | ||
| + | * [https://mml-book.github.io/book/mml-book.pdf Mathematics for Machine learning by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong, 2020] | ||
| + | * [https://klassfeldtheorie.files.wordpress.com/2018/10/mathematische-methoden-310117.pdf Mathematics for Physicists: Introductory Concepts and Methods by Alexander Altland & Jan von Delf, 2018] | ||
| + | * [http://users.isr.ist.utl.pt/~wurmd/Livros/school/Bishop%20-%20Pattern%20Recognition%20And%20Machine%20Learning%20-%20Springer%20%202006.pdf Bishop C.P. Pattern recognition and machine learning, Berlin: Springer, 2008.] | ||
| + | * [http://www.inference.org.uk/itprnn/book.pdf MackKay D. Information Theory, Pattern Recognition and Neural Networks, Inference.org.uk, 2009.] | ||
| + | |||
| + | =Linear algebra= | ||
*[https://drive.google.com/file/d/16SL9bQYar2ylDzHKNapBIDXCYUZEnRIh/view?fbclid=IwAR3fiuQgDJ0PRxv8o6UslbGx2ICdKxO2Li32FtwPJ_GbjRCXKhxa-BPZw2A Linear algebra by Jörg Liesen, Volker Mehrmann, 2015] | *[https://drive.google.com/file/d/16SL9bQYar2ylDzHKNapBIDXCYUZEnRIh/view?fbclid=IwAR3fiuQgDJ0PRxv8o6UslbGx2ICdKxO2Li32FtwPJ_GbjRCXKhxa-BPZw2A Linear algebra by Jörg Liesen, Volker Mehrmann, 2015] | ||
*[http://joshua.smcvt.edu/linearalgebra Linear algebra by Jim Hefferon, 2017] | *[http://joshua.smcvt.edu/linearalgebra Linear algebra by Jim Hefferon, 2017] | ||
*[https://web.stanford.edu/~boyd/vmls/?fbclid=IwAR08VCHfJ1hVAvuVBW6G59CZZ9EWzAlm0yKnID82DP9G2YbmugzsYIQQ4W0 Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares by Stephen Boyd and Lieven Vandenberghe, 2018] | *[https://web.stanford.edu/~boyd/vmls/?fbclid=IwAR08VCHfJ1hVAvuVBW6G59CZZ9EWzAlm0yKnID82DP9G2YbmugzsYIQQ4W0 Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares by Stephen Boyd and Lieven Vandenberghe, 2018] | ||
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| − | |||
=Basic statistics= | =Basic statistics= | ||
| − | = | + | =Bayesian statistics and inference= |
| − | |||
| − | |||
=Functional data analysis= | =Functional data analysis= | ||
* [https://www.unige.ch/~hairer/poly-sde-mani.pdf Solving Differential Equations on Manifolds by Ernst Hairer, 2011. University of Geneva] | * [https://www.unige.ch/~hairer/poly-sde-mani.pdf Solving Differential Equations on Manifolds by Ernst Hairer, 2011. University of Geneva] | ||
* | * | ||
| + | |||
| + | =Programming= | ||
| + | * [https://unglueit-files.s3.amazonaws.com/ebf/617027d14a3046998f54b31503ab7bca.pdf Python notes for professionals by GoalKicker.com Free Programming Books, 2020] | ||
| + | |||
| + | =Russian edition= | ||
| + | * [http://www.1variant.ru/content/uchebniki/matematika/650.pdf Лагутин М.Б. Наглядная математическая статистика, М.: Бином, 2009.] См. также [http://files.lbz.ru/pdf/cC2125-4-ch.pdf вырезку]. | ||
Revision as of 00:36, 30 December 2020
Contents
Machine learning for beginners
- A Brief Introduction to Machine Learning for Engineers by Osvaldo Simeone, 2017-2018
- Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz, Shai Ben-David, 2014
- Mathematics for Machine learning by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong, 2020
- Mathematics for Physicists: Introductory Concepts and Methods by Alexander Altland & Jan von Delf, 2018
- Bishop C.P. Pattern recognition and machine learning, Berlin: Springer, 2008.
- MackKay D. Information Theory, Pattern Recognition and Neural Networks, Inference.org.uk, 2009.
Linear algebra
- Linear algebra by Jörg Liesen, Volker Mehrmann, 2015
- Linear algebra by Jim Hefferon, 2017
- Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares by Stephen Boyd and Lieven Vandenberghe, 2018