Difference between revisions of "Week 1"

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|description=Course My first scientific paper: The goal of this week is to set up your tools, and to select your project}}
 
|description=Course My first scientific paper: The goal of this week is to set up your tools, and to select your project}}
  
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''The goal of this week'' is to set up your tools, and to select your project.  
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''The goal of this week'' is to set up your tools and select your project.
  
 
==Set the toolbox==  
 
==Set the toolbox==  
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#* and  an example of a [https://dblp.org/rec/journals/hisas/DorinKGS24.html?view=bibtex bibliographic record].
 
#* and  an example of a [https://dblp.org/rec/journals/hisas/DorinKGS24.html?view=bibtex bibliographic record].
 
# Create your draft LinkReview with an [https://docs.google.com/document/d/10JgJMieX13R5vlrCfJPrMqU9Rsd4c4JzaGytU8rWFE4/edit?usp=sharing example].
 
# Create your draft LinkReview with an [https://docs.google.com/document/d/10JgJMieX13R5vlrCfJPrMqU9Rsd4c4JzaGytU8rWFE4/edit?usp=sharing example].
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# Install bibliographic collection software [http://jabref.sourceforge.net/ JabRef].
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# Install the bibliographic collection software [http://jabref.sourceforge.net/ JabRef].
  
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===Collarobarion===
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===Collarobation===
 
#  Sign up [https://github.com/ GitHub].
 
#  Sign up [https://github.com/ GitHub].
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#* Set your address and login as: Name.Surname or Name-Surname.
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#* Set your username as: Name.Surname or Name-Surname.
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#* 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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#* Take a step in [https://guides.github.com/activities/hello-world/ GitHub introduction] and look through [https://guides.github.com/ the GitHub docs].  
 
# Download [https://desktop.github.com/ Desktop.GitHub], or use [https://cli.github.com/manual/ the command line CLI] to synchronize your project.
 
# Download [https://desktop.github.com/ Desktop.GitHub], or use [https://cli.github.com/manual/ the command line CLI] to synchronize your project.
 
#* Read the slides [http://www.machinelearning.ru/wiki/images/2/29/MMP_Praktikum317_2013s_VCS.pdf (Ru) Version Control System].
 
#* Read the slides [http://www.machinelearning.ru/wiki/images/2/29/MMP_Praktikum317_2013s_VCS.pdf (Ru) Version Control System].
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# Install [https://anaconda.org/anaconda/python Python Anaconda],  
 
# Install [https://anaconda.org/anaconda/python Python Anaconda],  
 
# install [https://www.jetbrains.com/pycharm/ PyCharm] or [https://code.visualstudio.com/ Visual Studio],  
 
# install [https://www.jetbrains.com/pycharm/ PyCharm] or [https://code.visualstudio.com/ Visual Studio],  
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# try [https://colab.research.google.com/notebooks/welcome.ipynb#recent=true Google Colab].
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# and try [https://colab.research.google.com/notebooks/welcome.ipynb#recent=true Google Colab].
 
# Look through [https://www.python.org/dev/peps/pep-0008/ Codestyle pep8].
 
# Look through [https://www.python.org/dev/peps/pep-0008/ Codestyle pep8].
  
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# Find public information about the experts and consultants.
 
# Find public information about the experts and consultants.
 
# Select your projects during the group discussion.
 
# Select your projects during the group discussion.
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# Wait for confirmation from '''the coordinator''' of your student group.
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# Wait for confirmation from your '''group coordinator''' of your student group.
 
# Politely write your consultant and discuss your project.
 
# Politely write your consultant and discuss your project.
  
 
==Homework==
 
==Homework==
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# Fill in the questionnaire of [https://forms.gle/FEJ28KEjxdj6Zgha7  Week 1: Imagine and plan a project]
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# Fill in the questionnaire for [https://forms.gle/FEJ28KEjxdj6Zgha7  Week 1: Imagine and plan a project]
 
# Rigorously follow the guide of Section [[Week_1#Select_your_project|Select your project]]
 
# Rigorously follow the guide of Section [[Week_1#Select_your_project|Select your project]]
 
# Take the steps of Section [[Week_1#Set_the_toolbox|Set the toolbox]]
 
# Take the steps of Section [[Week_1#Set_the_toolbox|Set the toolbox]]
 
# Write your coordinator and get access to the [https://github.com/intsystems GitHub repositories]
 
# Write your coordinator and get access to the [https://github.com/intsystems GitHub repositories]
 
# Open your notebook in the LinkReview format to gather your notes, thoughts, and references about your project.
 
# Open your notebook in the LinkReview format to gather your notes, thoughts, and references about your project.
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#* See more examples of LinkReview: [https://docs.google.com/document/d/1K7bIzU33MSfeUvg3WITRZX0pe3sibbtH62aw42wxsEI/edit?tab=t.0 one], [https://docs.google.com/document/d/1PflOzE5M3fD4BuChB0-OKnutdMrWBpuQAvkSwyBNv8Y/edit?tab=t.0 two], [https://docs.google.com/document/d/1b3ZF635fTWMtB35_slSHpfUMXgyFZAv7CpMUPhHQ5Hk/edit?tab=t.0#heading=h.beiz6lk1991d three].
  
 
==References to catch up==
 
==References to catch up==
 
# [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
 
# [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 Information Theory, Pattern Recognition and Neural Networks] by MackKay D., 2009
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# [http://www.inference.org.uk/itprnn/book.pdf Information Theory, Pattern Recognition and Neural Networks] by D. MackKay, 2009
 
# [https://arxiv.org/pdf/1709.02840 A Brief Introduction to Machine Learning for Engineers] by Osvaldo Simeone, 2018
 
# [https://arxiv.org/pdf/1709.02840 A Brief Introduction to Machine Learning for Engineers] by Osvaldo Simeone, 2018
 
# [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
 
# [https://mml-book.github.io/book/mml-book.pdf Mathematics for Machine Learning] by M. Peter et al.  
 
# [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] by Alexander Altland & Jan von Delf, 2017
 
# [https://klassfeldtheorie.files.wordpress.com/2018/10/mathematische-methoden-310117.pdf Mathematics for Physicists] by Alexander Altland & Jan von Delf, 2017
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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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# [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])

Latest revision as of 23:07, 21 February 2025

The goal of this week is to set up your tools and 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 the bibliographic collection software JabRef.

Collarobation

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

Homework

  1. Fill in the questionnaire for 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 D. MackKay, 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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