Difference between revisions of "Books"

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[[Media:DS2023program.pdf|Data Science: A Roadmap for Bachelor, Master, and Doctoral Degrees]]
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==Machine learning for beginners==
 
==Machine learning for beginners==
 
* [https://arxiv.org/pdf/1709.02840 A Brief Introduction to Machine Learning for Engineers by Osvaldo Simeone, 2017-2018]
 
* [https://arxiv.org/pdf/1709.02840 A Brief Introduction to Machine Learning for Engineers by Osvaldo Simeone, 2017-2018]

Revision as of 22:39, 20 February 2023

Data Science: A Roadmap for Bachelor, Master, and Doctoral Degrees

Machine learning for beginners

Linear algebra

Optimization

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

Functional data analysis

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

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