Difference between revisions of "Todo list"

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== Todo 0: Prepare necessary tools ==  
 
== Todo 0: Prepare necessary tools ==  
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# '''Editing'''. Install LaTeX: [http://miktex.org MikTeX] for Windown, [http://www.tug.org/texlive/ TeX Live] for Linux, and for Mac OS. Sign up [https://v2.overleaf.com/ V2 OverLeaf  ShareLaTeX].
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# Install the editor [http://www.texniccenter.org/ TeXnic Center] or its alternative [http://www.winedt.com/ WinEdt] for Windows, [http://www.tug.org/texworks/ TeXworks] for Linux, and [https://www.xm1math.net/texmaker/ TeXmaker]for Mac OS.
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#* Read [[LaTeX|LaTeX on MachineLearning]] (Ru).
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#* Useful: [https://en.wikibooks.org/wiki/LaTeX Wikibooks LaTeX], [[Media:Voron05latex.pdf|''К.В.Воронцов.'' LaTeX2e в примерах]].
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#* Read ''Львовский С. М.'' [http://www.mccme.ru/free-books/llang/newllang.pdf Набор и верстка в системе LaTeX].
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# Download [[Media:jmlda-guides.zip‎‎|the paper template, ZIP]] and compile it.
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# Read [http://en.wikipedia.org/wiki/Bibtex BibTeX].
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#* [http://liinwww.ira.uka.de/csbib?strijov%20nonlinear An example of a bibliographic database].
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#* [http://liinwww.ira.uka.de/cgi-bin/bibshow?e=Njtd0ECMQ03121/fyqboefe%7d81352582&r=bibtex&mode=intra An example of a biliographic record].
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#* [https://docs.google.com/document/d/10JgJMieX13R5vlrCfJPrMqU9Rsd4c4JzaGytU8rWFE4/edit?usp=sharing An example of draft revirew LinkReview].
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#* [http://en.wikipedia.org/wiki/List_of_academic_databases_and_search_engines List of databasea and search engines].
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#* [https://en.wikipedia.org/wiki/List_of_datasets_for_machine_learning_research List of datasets for Machine Learning projects].
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# Install bibliographic collection software [http://jabref.sourceforge.net/ JabRef] (can be postponed).
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# '''Communications'''. Sign up [https://github.com/ GitHub].
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#* Inportant: address and login like Name.Surname or Name-Surname (it depends on system conventions) is welcome.
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#* Introductory sliders [[Media:MMP_Praktikum317_2013s_VCS.pdf|on Version Control System]].
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#* Introduction to [https://guides.github.com/ GitHub].
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#* The first steps in [https://guides.github.com/activities/hello-world/ GitHub].
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# Download a shell: [https://desktop.github.com/ Desktop.GitHub], or use a command line to synchronise your project.
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# Sign up [http://www.machinelearning.ru/ MachineLearning.ru]. Send a logon to your coordinator of to mlalgorithms [at] gmail [dot] com.
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# To state a problem (write essay) using notebook [https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Typesetting%20Equations.html see example] in MathJax.
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#* Create your page [[Участник:Anastasiya|example]].
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<!-- # Поставить ссылку на личную страницу со своей фамилии в таблице на странице группы.-->
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# Install [https://hangouts.google.com/ Hangouts], [[Скайп (Skype)|read instructions]].
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# '''Programming'''. Install Python [https://anaconda.org/anaconda/python Anakonda], [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].
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#* Development for ML: Pytorch
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#* Style formatting: Codestyle pep8
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# '''Add.''' As alternative install and try [[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].
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#* Read [[Matlab|Introducton to Matlab]].
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#* Read [[Документирование функций Matlab|Matlab code style, reporting and documenting]].
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#* Read [[Media: MatlabStyle1p5.pdf|Matlab Programming Style Guidelines]].
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# '''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].
  
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'''Resources'''
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* Announcenents: Telegram [http://t.me/AutomationML AutomationML]
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* Ask to email mlalgorithms [at] gmail [dot] com
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* [https://github.com/Strijov/Strijov2018-1AutomationOfResearch/raw/master/Strijov2018_1AutomationOfResearch.pdf  Slides].
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* [http://svn.code.sf.net/p/mvr/code/lectures/MLEducation/Strijov2014MLCourseShort.pdf?format=raw Short course description].
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* Progress questionary '''[https://goo.gl/forms/jPbh92DOfTrwpyTF3 Todo 1]'''.
  
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'''References to catch up'''
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* [https://arxiv.org/pdf/1709.02840 A Brief Introduction to Machine Learning for Engineers by Osvaldo Simeone, 2017-2018]
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* [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]
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* [https://mml-book.github.io/book/mml-book.pdf Mathematics for Machine learning by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong]
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* [https://klassfeldtheorie.files.wordpress.com/2018/10/mathematische-methoden-310117.pdf Mathematics for Physicists: Introductory Concepts and Methods by Alexander Altland & Jan von Delf]
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* [https://unglueit-files.s3.amazonaws.com/ebf/617027d14a3046998f54b31503ab7bca.pdf Python notes for professionals by GoalKicker.com Free Programming Books.]
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* [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].
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* [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.]
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* [http://www.inference.org.uk/itprnn/book.pdf MackKay D. Information Theory, Pattern Recognition and Neural Networks, Inference.org.uk, 2009.]
  
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'''Questionnaries'''
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* [https://goo.gl/forms/es2dEL9qBAtlYfbL2 Todo list 1: Prepare necessary tools]
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* [https://goo.gl/forms/Z19P6Rufll0nL06a2 Select problems]
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http://svn.code.sf.net/p/mvr/code/lectures/MLEducation/Strijov2014MLCourseShort_eng.pdf?format=raw
  
 
== Todo A: Write an abstract ==
 
== Todo A: Write an abstract ==

Revision as of 22:51, 12 February 2020

The todo lists here corresponds to the Course schedule. Each list must be completed before the day of review. It is Wednesday 06:00 am for the 2020 Spring semester.

Todo 0: Prepare necessary tools

  1. Editing. 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. Download the paper template, ZIP and compile it.
  4. Read BibTeX.
  5. Install bibliographic collection software JabRef (can be postponed).
  6. Communications. Sign up GitHub.
    • Inportant: 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.
  7. Download a shell: Desktop.GitHub, or use a command line to synchronise your project.
  8. Sign up MachineLearning.ru. Send a logon to your coordinator of to mlalgorithms [at] gmail [dot] com.
  9. To state a problem (write essay) using notebook see example in MathJax.
  10. Install Hangouts, read instructions.
  11. Programming. Install Python Anakonda, PyCharm (alternative Visual Studio), Notebook online Google.Colab.
    • Development for ML: Pytorch
    • Style formatting: Codestyle pep8
  12. Add. As alternative install and try Matlab (MIPT provides free version), (alternative Octave), R-project, Wofram Mathematica.
  13. Add. Read with pleasure Кутателадзе С. С. Советы эпизодическому переводчику and Сосинский А. Б. Как написать математическую статью по-английски.

Resources

References to catch up

Questionnaries

http://svn.code.sf.net/p/mvr/code/lectures/MLEducation/Strijov2014MLCourseShort_eng.pdf?format=raw

Todo A: Write an abstract

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