Difference between revisions of "Week 1"

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==Set the toolbox==  
 
==Set the toolbox==  
 
=== LaTeX ===
 
=== LaTeX ===
−
# Install the LaTeX compliler: [http://miktex.org MikTeX] for Windows, [http://www.tug.org/texlive/ TeX Live] for Linux, and Mac OS. Sign up [https://v2.overleaf.com/ OverLeaf].
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# Install the LaTeX compiler: [http://miktex.org MikTeX] for Windows, [http://www.tug.org/texlive/ TeX Live] for Linux, and Mac OS. Sign up [https://v2.overleaf.com/ OverLeaf].
−
# 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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# Install the editor [http://www.texniccenter.org/ TeXnic Center] or [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.
 
# Read [https://tobi.oetiker.ch/lshort/lshort.pdf Introduction to LATEX] by Oetker et al., 2023 or (Ru [http://www.mccme.ru/free-books/llang/newllang.pdf Львовский С.М.].
 
# Read [https://tobi.oetiker.ch/lshort/lshort.pdf Introduction to LATEX] by Oetker et al., 2023 or (Ru [http://www.mccme.ru/free-books/llang/newllang.pdf Львовский С.М.].
−
# 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]
+
# Download the [https://github.com/vadim-vic/the-Art-homework?tab=readme-ov-file 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]
  
 
=== BibTeX ===
 
=== BibTeX ===
 
# Read [http://en.wikipedia.org/wiki/Bibtex BibTeX on Wiki].
 
# Read [http://en.wikipedia.org/wiki/Bibtex BibTeX on Wiki].
 
<!-- # [http://en.wikipedia.org/wiki/List_of_academic_databases_and_search_engines List of databases and search engines].-->
 
<!-- # [http://en.wikipedia.org/wiki/List_of_academic_databases_and_search_engines List of databases and search engines].-->
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#* See an example [https://dblp.org/ of a bibliographic database]
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#* See an example of a  [https://dblp.org/ bibliographic database]
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#* and  an example [https://dblp.org/rec/journals/hisas/DorinKGS24.html?view=bibtex of a bibliographic record].
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#* and  an example of a [https://dblp.org/rec/journals/hisas/DorinKGS24.html?view=bibtex bibliographic record].
−
# Create your draft LinkReview with [https://docs.google.com/document/d/10JgJMieX13R5vlrCfJPrMqU9Rsd4c4JzaGytU8rWFE4/edit?usp=sharing an example].
+
# Create your draft LinkReview with an [https://docs.google.com/document/d/10JgJMieX13R5vlrCfJPrMqU9Rsd4c4JzaGytU8rWFE4/edit?usp=sharing example].
 
# Install bibliographic collection software [http://jabref.sourceforge.net/ JabRef].
 
# Install bibliographic collection software [http://jabref.sourceforge.net/ JabRef].
  
 
===Collarobarion===
 
===Collarobarion===
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#  Sign up [https://github.com/ GitHub]  
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#  Sign up [https://github.com/ GitHub].
 
#* Set your address and login as: Name.Surname or Name-Surname.
 
#* Set your address and login as: Name.Surname or Name-Surname.
 
#* Thake a step in [https://guides.github.com/activities/hello-world/ GitHub introduction] and look through [https://guides.github.com/ the GitHub docs].  
 
#* Thake a step in [https://guides.github.com/activities/hello-world/ GitHub introduction] and look through [https://guides.github.com/ the GitHub docs].  
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==References to catch up==
 
==References to catch up==
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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] or see [https://www.bishopbook.com/ the version 2024] on Deep Learning
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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 Pattern recognition and machine learning] by C.P. Bishop, or the version  on [https://www.bishopbook.com/ Deep Learning], 2024
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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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# [http://www.inference.org.uk/itprnn/book.pdf Information Theory, Pattern Recognition and Neural Networks] by  MackKay D., 2009
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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://arxiv.org/pdf/1709.02840 A Brief Introduction to Machine Learning for Engineers] by Osvaldo Simeone, 2018
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# [https://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz, Shai Ben-David, 2014]
+
# [https://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf 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://mml-book.github.io/book/mml-book.pdf Mathematics for Machine Learning] by M. Peter et al.  
−
# [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://klassfeldtheorie.files.wordpress.com/2018/10/mathematische-methoden-310117.pdf Mathematics for Physicists] by Alexander Altland & Jan von Delf, 2017
−
# [https://unglueit-files.s3.amazonaws.com/ebf/617027d14a3046998f54b31503ab7bca.pdf Python notes for professionals by GoalKicker.com Free Programming Books.]
+
# [https://unglueit-files.s3.amazonaws.com/ebf/617027d14a3046998f54b31503ab7bca.pdf Python notes for professionals]  by GoalKicker.com Free Programming Books
 
# Computer Mathematics by D.J. Cooke and H.E. Bez, 1984 (Ru [https://www.phantastike.com/math/comriuternaya_matematika_cooke/pdf/ Кук, Бейз])
 
# Computer Mathematics by D.J. Cooke and H.E. Bez, 1984 (Ru [https://www.phantastike.com/math/comriuternaya_matematika_cooke/pdf/ Кук, Бейз])

Revision as of 21:13, 21 February 2025

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

Set the toolbox

LaTeX

  1. Install the LaTeX compiler: MikTeX for Windows, TeX Live for Linux, and Mac OS. Sign up OverLeaf.
  2. Install the editor TeXnic Center or WinEdt for Windows, TeXworks for Linux, and TeXmaker for Mac OS.
  3. Read Introduction to LATEX by Oetker et al., 2023 or (Ru Львовский С.М..
  4. Download the paper template and compile it. You need two files: .tex and .bib

BibTeX

  1. Read BibTeX on Wiki.
  2. Create your draft LinkReview with an example.
  3. Install bibliographic collection software JabRef.

Collarobarion

  1. Sign up GitHub.
  2. Download Desktop.GitHub, or use the command line CLI to synchronize your project.
  3. Send your login name to your group coordinator to join /github.com/intsystems.

Programming

  1. Install Python Anaconda,
  2. install PyCharm or Visual Studio,
  3. try Google Colab.
  4. Look through Codestyle pep8.

To be informed of the variety of programming languages try one of the following online compiles: Matlab, Mathematica, the Julia language, the R project.

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 coordinator of your student group.
  5. Politely write your consultant and discuss your project.

Homework

  1. Fill in the questionnaire of Week 1: Imagine and plan a project
  2. Rigorously follow the guide of Section Select your project
  3. Take the steps of Section Set the toolbox
  4. Write your coordinator and get access to the GitHub repositories
  5. Open your notebook in the LinkReview format to gather your notes, thoughts, and references about your project.

References to catch up

  1. Pattern recognition and machine learning by C.P. Bishop, or the version on Deep Learning, 2024
  2. Information Theory, Pattern Recognition and Neural Networks by MackKay D., 2009
  3. A Brief Introduction to Machine Learning for Engineers by Osvaldo Simeone, 2018
  4. Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz, Shai Ben-David, 2014
  5. Mathematics for Machine Learning by M. Peter et al.
  6. Mathematics for Physicists by Alexander Altland & Jan von Delf, 2017
  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)
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