Difference between revisions of "Week 1"

From Research management course
Jump to: navigation, search
Line 9: Line 9:
 
#* Useful: [https://en.wikibooks.org/wiki/LaTeX Wikibooks LaTeX], [http://www.machinelearning.ru/wiki/images/e/e4/LaTeX_examples.pdf К.В.Воронцов. LaTeX2e в примерах].
 
#* Useful: [https://en.wikibooks.org/wiki/LaTeX Wikibooks LaTeX], [http://www.machinelearning.ru/wiki/images/e/e4/LaTeX_examples.pdf К.В.Воронцов. LaTeX2e в примерах].
 
#* Read ''Львовский С.М.'' [http://www.mccme.ru/free-books/llang/newllang.pdf Набор и верстка в системе LaTeX] (Ru).
 
#* Read ''Львовский С.М.'' [http://www.mccme.ru/free-books/llang/newllang.pdf Набор и верстка в системе LaTeX] (Ru).
−
#* Read ''Мильчин А.Э. Чельцова Л.К. ''[https://orfogrammka.ru/%D1%81%D0%BF%D1%80%D0%B0%D0%B2%D0%BE%D1%87%D0%BD%D0%B8%D0%BA/%D1%81%D0%BF%D1%80%D0%B0%D0%B2%D0%BE%D1%87%D0%BD%D0%B8%D0%BA_%D0%B8%D0%B7%D0%B4%D0%B0%D1%82%D0%B5%D0%BB%D1%8F_%D0%B8_%D0%B0%D0%B2%D1%82%D0%BE%D1%80%D0%B0_%D0%BC%D0%B8%D0%BB%D1%8C%D1%87%D0%B8%D0%BD_%D1%87%D0%B5%D0%BB%D1%8C%D1%86%D0%BE%D0%B2%D0%B0/  Справочник издателя и автора] (Ru).
+
#* Note ''Мильчин А.Э. Чельцова Л.К. ''[https://orfogrammka.ru/%D1%81%D0%BF%D1%80%D0%B0%D0%B2%D0%BE%D1%87%D0%BD%D0%B8%D0%BA/%D1%81%D0%BF%D1%80%D0%B0%D0%B2%D0%BE%D1%87%D0%BD%D0%B8%D0%BA_%D0%B8%D0%B7%D0%B4%D0%B0%D1%82%D0%B5%D0%BB%D1%8F_%D0%B8_%D0%B0%D0%B2%D1%82%D0%BE%D1%80%D0%B0_%D0%BC%D0%B8%D0%BB%D1%8C%D1%87%D0%B8%D0%BD_%D1%87%D0%B5%D0%BB%D1%8C%D1%86%D0%BE%D0%B2%D0%B0/  Справочник издателя и автора] (Ru).
−
# Download [http://jmlda.org/papers/doc/jmlda-guides.zip the paper template, ZIP] and compile it.
 
−
# '''References'''. Read [http://en.wikipedia.org/wiki/Bibtex BibTeX].
 
−
#* [http://liinwww.ira.uka.de/csbib?strijov%20nonlinear An example of a bibliographic database].
 
−
#* [http://liinwww.ira.uka.de/cgi-bin/bibshow?e=Njtd0ECMQ03121/fyqboefe%7d81352582&r=bibtex&mode=intra An example of a bibliographic record].
 
−
#* [https://docs.google.com/document/d/10JgJMieX13R5vlrCfJPrMqU9Rsd4c4JzaGytU8rWFE4/edit?usp=sharing An example of draft review LinkReview].
 
−
#* [http://en.wikipedia.org/wiki/List_of_academic_databases_and_search_engines List of databases and search engines].
 
−
#* [https://en.wikipedia.org/wiki/List_of_datasets_for_machine_learning_research List of data-sets for Machine Learning projects].
 
−
# Install bibliographic collection software [http://jabref.sourceforge.net/ JabRef] (can be postponed).
 
−
# '''Communications'''. Sign up [https://github.com/ GitHub].
 
−
#* Important: address and login like Name.Surname or Name-Surname (it depends on system conventions) is welcome.
 
−
#* Introductory sliders [http://www.machinelearning.ru/wiki/images/2/29/MMP_Praktikum317_2013s_VCS.pdf on Version Control System].
 
−
#* Introduction to [https://guides.github.com/ GitHub].
 
−
#* The first steps in [https://guides.github.com/activities/hello-world/ GitHub].
 
−
# Download a shell: [https://desktop.github.com/ Desktop.GitHub], or use a command line to synchronise your project.
 
−
# Sign up [http://www.machinelearning.ru/ MachineLearning.ru]. Send your login name to your coordinator or to mlalgorithms [at] gmail [dot] com.
 
−
# Create your page [http://www.machinelearning.ru/wiki/index.php?title=%D0%A3%D1%87%D0%B0%D1%81%D1%82%D0%BD%D0%B8%D0%BA:Anastasiya example].
 
−
<!--# To state a problem (write essay) using notebook [https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Typesetting%20Equations.html see example] in MathJax.-->
 
−
<!-- # Поставить ссылку на личную страницу со своей фамилии в таблице на странице группы.-->
 
−
<!--# Install [https://hangouts.google.com/ Hangouts], [http://www.machinelearning.ru/wiki/index.php?title=%D0%A1%D0%BA%D0%B0%D0%B9%D0%BF_%28Skype%29 Skype - read instructions].-->
 
−
# '''Programming'''. Install Python [https://anaconda.org/anaconda/python Anaconda], [https://www.jetbrains.com/pycharm/ PyCharm] (alternative [https://code.visualstudio.com/ Visual Studio]), Notebook online [https://colab.research.google.com/notebooks/welcome.ipynb#recent=true Google.Colab].
 
−
#* Development for ML: [https://pytorch.org/ PyTorch]
 
−
#* Style formatting: [https://www.python.org/dev/peps/pep-0008/ Codestyle pep8]
 
−
# '''Add.''' As alternative install and try [http://www.machinelearning.ru/wiki/index.php?title=Matlab Matlab (MIPT provides free version)], (alternative [http://www.gnu.org/software/octave/ Octave]), [https://www.r-project.org/ R-project], [https://www.wolframcloud.com/ Wofram Mathematica].
 
−
#* Read [http://www.machinelearning.ru/wiki/images/archive/f/fc/20150209132356%21Voron-ML-Intro-slides.pdf Introduction to Matlab]].
 
−
#* Read [http://www.machinelearning.ru/wiki/index.php?title=%D0%94%D0%BE%D0%BA%D1%83%D0%BC%D0%B5%D0%BD%D1%82%D0%B8%D1%80%D0%BE%D0%B2%D0%B0%D0%BD%D0%B8%D0%B5_%D1%84%D1%83%D0%BD%D0%BA%D1%86%D0%B8%D0%B9_Matlab Matlab code style, reporting and documenting]].
 
−
#* Read [http://www.machinelearning.ru/wiki/images/1/18/MatlabStyle1p5.pdf Matlab Programming Style Guidelines].
 
−
# '''Add.''' Read with pleasure [http://www.math.nsc.ru/LBRT/g2/english/ssk/r-e.pdf Кутателадзе С. С. Советы эпизодическому переводчику] and [http://www.ega-math.narod.ru/Quant/ABS.htm Сосинский А. Б. Как написать математическую статью по-английски] (Ru).
 
−
 
 
−
==Resources==
 
−
# [Slides for week 0].
 
−
# [Video for week 0].
 
−
# [Slides for week 1].
 
−
# [Video for week 1].
 
−
# [http://svn.code.sf.net/p/mvr/code/lectures/MLEducation/Strijov2014MLCourseShort.pdf?format=raw Short course description].
 
−
 
 
−
==References to catch up==
 
−
# [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]
 
−
# [https://klassfeldtheorie.files.wordpress.com/2018/10/mathematische-methoden-310117.pdf Mathematics for Physicists: Introductory Concepts and Methods by Alexander Altland & Jan von Delf]
 
−
# [https://unglueit-files.s3.amazonaws.com/ebf/617027d14a3046998f54b31503ab7bca.pdf Python notes for professionals by GoalKicker.com Free Programming Books.]
 
−
# [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] (Ru)
 
−
# [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]).
 
−
#* Read ''Львовский С.М.'' [http://www.mccme.ru/free-books/llang/newllang.pdf Набор и верстка в системе LaTeX] (Ru).
 
−
#* Read ''Мильчин А.Э. Чельцова Л.К. ''[https://orfogrammka.ru/%D1%81%D0%BF%D1%80%D0%B0%D0%B2%D0%BE%D1%87%D0%BD%D0%B8%D0%BA/%D1%81%D0%BF%D1%80%D0%B0%D0%B2%D0%BE%D1%87%D0%BD%D0%B8%D0%BA_%D0%B8%D0%B7%D0%B4%D0%B0%D1%82%D0%B5%D0%BB%D1%8F_%D0%B8_%D0%B0%D0%B2%D1%82%D0%BE%D1%80%D0%B0_%D0%BC%D0%B8%D0%BB%D1%8C%D1%87%D0%B8%D0%BD_%D1%87%D0%B5%D0%BB%D1%8C%D1%86%D0%BE%D0%B2%D0%B0/  Справочник издателя и автора] (Ru).
 
 
# Download [http://jmlda.org/papers/doc/jmlda-guides.zip the paper template, ZIP] and compile it.
 
# Download [http://jmlda.org/papers/doc/jmlda-guides.zip the paper template, ZIP] and compile it.
 
# '''References'''. Read [http://en.wikipedia.org/wiki/Bibtex BibTeX].
 
# '''References'''. Read [http://en.wikipedia.org/wiki/Bibtex BibTeX].

Revision as of 18:32, 9 February 2021

Set the toolbox

  1. Editors. Install LaTeX: MikTeX for Windown, TeX Live for Linux, and for Mac OS. Sign up V2 OverLeaf ShareLaTeX.
  2. Install the editor TeXnic Center or its alternative WinEdt for Windows, TeXworks for Linux, and TeXmakerfor Mac OS.
  3. Editors. Install LaTeX: MikTeX for Windown, TeX Live for Linux, and for Mac OS. Sign up V2 OverLeaf ShareLaTeX.
  4. Install the editor TeXnic Center or its alternative WinEdt for Windows, TeXworks for Linux, and TeXmakerfor Mac OS.
  5. Download the paper template, ZIP and compile it.
  6. References. Read BibTeX.
  7. Install bibliographic collection software JabRef (can be postponed).
  8. Communications. Sign up GitHub.
    • Important: address and login like Name.Surname or Name-Surname (it depends on system conventions) is welcome.
    • Introductory sliders on Version Control System.
    • Introduction to GitHub.
    • The first steps in GitHub.
  9. Download a shell: Desktop.GitHub, or use a command line to synchronise your project.
  10. Sign up MachineLearning.ru. Send your login name to your coordinator or to mlalgorithms [at] gmail [dot] com.
  11. Create your page example.
  12. Programming. Install Python Anaconda, PyCharm (alternative Visual Studio), Notebook online Google.Colab.
  13. Add. As alternative install and try Matlab (MIPT provides free version), (alternative Octave), R-project, Wofram Mathematica.
  14. Add. Read with pleasure Кутателадзе С. С. Советы эпизодическому переводчику and Сосинский А. Б. Как написать математическую статью по-английски (Ru).

Resources

  1. Slides for week 0.
  2. Video for week 0.
  3. [Slides for week 1].
  4. [Video for week 1].
  5. Short course description.

References to catch up

  1. A Brief Introduction to Machine Learning for Engineers by Osvaldo Simeone, 2017-2018
  2. Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz, Shai Ben-David, 2014
  3. Mathematics for Machine learning by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong
  4. Mathematics for Physicists: Introductory Concepts and Methods by Alexander Altland & Jan von Delf
  5. Python notes for professionals by GoalKicker.com Free Programming Books.
  6. Лагутин М.Б. Наглядная математическая статистика, М.: Бином, 2009. См. также вырезку (Ru)
  7. Bishop C.P. Pattern recognition and machine learning, Berlin: Springer, 2008
  8. MackKay D. Information Theory, Pattern Recognition and Neural Networks, Inference.org.uk, 2009
Retrieved from ‘https://m1p.org/index.php?title=Week_1&oldid=436’