Difference between revisions of "Books"
From Research management course
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* [https://archive.siam.org/books/textbooks/fr18_book.pdf Iterative Methods for Optimization by C.T.Kelley, 1999] | * [https://archive.siam.org/books/textbooks/fr18_book.pdf Iterative Methods for Optimization by C.T.Kelley, 1999] | ||
| − | = | + | =Basics of probability and statistics= |
| − | * Probability | + | * A first course in probability by Sheldon M. Ross, 2012 |
| − | * Mathematical statistics by | + | * Elements of information theory by Thomas M. Cover, Joy A. Thomas, 2006 |
| + | * Probability theory by Alexandr A. Borovkov, 2006 | ||
| + | * Mathematical statistics by Alexandr A. Borovkov, 1999 | ||
* Linear Statistical Inference & Its Applications by C. Radhakrishna Rao, 1967 | * Linear Statistical Inference & Its Applications by C. Radhakrishna Rao, 1967 | ||
* Linear Models and Generalizations: Least Squares and Alternatives by C. Radhakrishna Rao et al., 2007 | * Linear Models and Generalizations: Least Squares and Alternatives by C. Radhakrishna Rao et al., 2007 | ||
| Line 30: | Line 32: | ||
=Functional data analysis= | =Functional data analysis= | ||
| + | * Sequences and series in banach spaces by J. Diestel, 1984 | ||
* Functional data analysis by J.O. Ramsay and B.W. Silverman, 2005 | * Functional data analysis by J.O. Ramsay and B.W. Silverman, 2005 | ||
* [https://www.unige.ch/~hairer/poly-sde-mani.pdf Solving Differential Equations on Manifolds by Ernst Hairer, 2011] | * [https://www.unige.ch/~hairer/poly-sde-mani.pdf Solving Differential Equations on Manifolds by Ernst Hairer, 2011] | ||
| + | |||
| + | ==Discrete analysis== | ||
| + | * Lectures on discrete geometry by Jiří Matoušek, 2002 | ||
| + | * Indiscrete thoughts by Gian-Carlo Rota, 2008 | ||
| + | * Graph theory by Reinhard Diestel, 2017 | ||
| + | * Graph theory (groups and symmetries: from finite groups to Lie groups) by Reinhard Diestel, 2000 | ||
=Programming= | =Programming= | ||
* [https://unglueit-files.s3.amazonaws.com/ebf/617027d14a3046998f54b31503ab7bca.pdf Python notes for professionals by GoalKicker.com Free Programming Books, 2020] | * [https://unglueit-files.s3.amazonaws.com/ebf/617027d14a3046998f54b31503ab7bca.pdf Python notes for professionals by GoalKicker.com Free Programming Books, 2020] | ||
* [https://d2l.ai/ Dive into Deep Learning by Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola, 2020] | * [https://d2l.ai/ Dive into Deep Learning by Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola, 2020] | ||
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=Russian edition= | =Russian edition= | ||
* [http://www.1variant.ru/content/uchebniki/matematika/650.pdf Лагутин М.Б. Наглядная математическая статистика, 2009] (cм. также [http://files.lbz.ru/pdf/cC2125-4-ch.pdf вырезку]) | * [http://www.1variant.ru/content/uchebniki/matematika/650.pdf Лагутин М.Б. Наглядная математическая статистика, 2009] (cм. также [http://files.lbz.ru/pdf/cC2125-4-ch.pdf вырезку]) | ||
* [https://www.artlebedev.ru/izdal/spravochnik-izdatelya-i-avtora/ Аркадий Мильчин и Людмила Чельцова. Справочник издателя и автора (Редакционно-издательское оформление издания), 2018] | * [https://www.artlebedev.ru/izdal/spravochnik-izdatelya-i-avtora/ Аркадий Мильчин и Людмила Чельцова. Справочник издателя и автора (Редакционно-издательское оформление издания), 2018] | ||
Revision as of 23:38, 5 April 2021
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
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie Robert Tibshirani Jerome Friedman, 2008
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
Optimization
- Convex Optimization by Stephen Boyd and Lieven Vandenberghe, 2009
- Iterative Methods for Optimization by C.T.Kelley, 1999
Basics of probability and statistics
- A first course in probability by Sheldon M. Ross, 2012
- Elements of information theory by Thomas M. Cover, Joy A. Thomas, 2006
- Probability theory by Alexandr A. Borovkov, 2006
- Mathematical statistics by Alexandr A. Borovkov, 1999
- Linear Statistical Inference & Its Applications by C. Radhakrishna Rao, 1967
- Linear Models and Generalizations: Least Squares and Alternatives by C. Radhakrishna Rao et al., 2007
Bayesian statistics and inference
- Bayesian reasoning and machine learning by David Barber, 2014
- Probabilistic graphical models by Daphne Koller and Nir Friedman, 2009
- Machine learning: a probabilistic perspective by Kevin P. Murphy, 2012
- Bayesian data analysis by Andrew Gelman et al., 2013
Functional data analysis
- Sequences and series in banach spaces by J. Diestel, 1984
- Functional data analysis by J.O. Ramsay and B.W. Silverman, 2005
- Solving Differential Equations on Manifolds by Ernst Hairer, 2011
Discrete analysis
- Lectures on discrete geometry by Jiří Matoušek, 2002
- Indiscrete thoughts by Gian-Carlo Rota, 2008
- Graph theory by Reinhard Diestel, 2017
- Graph theory (groups and symmetries: from finite groups to Lie groups) by Reinhard Diestel, 2000
Programming
- Python notes for professionals by GoalKicker.com Free Programming Books, 2020
- Dive into Deep Learning by Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola, 2020