Difference between revisions of "Week 1"

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#* 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] (Ru).  
 
#* 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] (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).
 
#* 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.
+
# Download the [https://github.com/vadim-vic/the-Art-homework?tab=readme-ov-file the paper template] and compile it. You need two files: [https://github.com/vadim-vic/the-Art-homework/blob/main/Name-Step-1.tex .tex] and [https://github.com/vadim-vic/the-Art-homework/blob/main/Name-theArt.bib .bib]
 
# '''References'''. Read [http://en.wikipedia.org/wiki/Bibtex BibTeX].
 
# '''References'''. Read [http://en.wikipedia.org/wiki/Bibtex BibTeX].
 
#* [https://dblp.org/ An example of a bibliographic database].
 
#* [https://dblp.org/ An example of a bibliographic database].

Revision as of 17:54, 21 February 2025

The goal of this week is to set up your tools, and to select your project.

Set the toolbox

  1. Editors. Install LaTeX: MikTeX for Windows, TeX Live for Linux, and 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 the paper template and compile it. You need two files: .tex and .bib
  4. References. Read BibTeX.
  5. Install bibliographic collection software JabRef.
  6. Communications. Sign up GitHub.
    • Run GitHub Copilot
    • Important: address and login like Name.Surname or Name-Surname (it depends on system conventions) is welcome.
    • Introductory sliders on Version Control System (ru).
    • Introduction to GitHub.
    • The first steps in GitHub.
  7. Download a shell: Desktop.GitHub, or use the command line CLI to synchronize your project.
  8. Sign up MachineLearning.ru. Send your login name to your coordinator (or to mlalgorithms [at] gmail [dot] com; to find the coordinator).
  9. Programming. Install Python Anaconda, PyCharm (alternative Visual Studio), Notebook online Google.Colab.
  10. Add. As alternative install and try Matlab (check of your university provides a free version), (alternative Octave), R-project, Wolfram Mathematica.
  11. Add. See The Julia language and R project
  12. Add. Read with pleasure Кутателадзе С. С. Советы эпизодическому переводчику and Сосинский А. Б. Как написать математическую статью по-английски (Ru).

Select your project

To select your project:

  1. Look through the list of projects (Spring 2025).
  2. Find public information about the experts and consultants.
  3. Select your projects during the group discussion.
  4. Wait for confirmation from the responsible coordinator of your student group
  5. Put confirmed topics Group table (Spring 2025).
  6. Politely write your consultant and discuss your project.

Resources

References to catch up

  1. Bishop C.P. Pattern recognition and machine learning, Berlin: Springer, 2008 or see the version 2024 on Deep Learning
  2. MackKay D. Information Theory, Pattern Recognition and Neural Networks, Inference.org.uk, 2009
  3. A Brief Introduction to Machine Learning for Engineers by Osvaldo Simeone, 2017-2018
  4. Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz, Shai Ben-David, 2014
  5. Mathematics for Machine Learning by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong
  6. Mathematics for Physicists: Introductory Concepts and Methods by Alexander Altland & Jan von Delf
  7. Python notes for professionals by GoalKicker.com Free Programming Books.
  8. Computer Mathematics by D.J. Cooke and H.E. Bez, 1984 (Ru Кук, Бейз)

Homework

  1. Fill in the questionnaire of Week 1: Imagine and plan a project
  2. Run all steps of Section Select your project
  3. Rigorously follow all the steps of Section Set the toolbox
  4. Write your coordinator and get access to the GitHub
  5. Join your inherited project repository (recommended) or create a new one (here will be the template)