Difference between revisions of "Week 1"
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===Programming=== | ===Programming=== | ||
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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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# Politely write your consultant and discuss your project. | # Politely write your consultant and discuss your project. | ||
| − | == | + | ==Homework== |
| − | + | # Fill in the questionnaire of [https://forms.gle/FEJ28KEjxdj6Zgha7 Week 1: Imagine and plan a project] | |
| − | + | # Run all steps of Section [[Week_1#Select_your_project|Select your project]] | |
| − | + | # Rigorously follow all the steps of Section [[Week_1#Set_the_toolbox|Set the toolbox]] | |
| − | + | # Write your coordinator and get access to the GitHub | |
| − | + | # Open your notebook in the LinkReview format to gather your notes, thoughts, and references about your project. | |
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==References to catch up== | ==References to catch up== | ||
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# [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]) | ||
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Revision as of 20:57, 21 February 2025
The goal of this week is to set up your tools, and to select your project.
Contents
Set the toolbox
LaTeX
- Install the LaTeX compliler: MikTeX for Windows, TeX Live for Linux, and Mac OS. Sign up OverLeaf.
- Install the editor TeXnic Center or its alternative WinEdt for Windows, TeXworks for Linux, and TeXmakerfor Mac OS.
- Read Introduction to LATEX by Oetker et al., 2023 or (Ru Львовский С.М..
- Download the the paper template and compile it. You need two files: .tex and .bib
BibTeX
- Read BibTeX on Wiki.
- See an example of a bibliographic database
- and an example of a bibliographic record.
- Create your draft LinkReview with an example.
- Install bibliographic collection software JabRef.
Collarobarion
- Sign up GitHub
- Set your address and login as: Name.Surname or Name-Surname.
- Thake a step in GitHub introduction and look through the GitHub docs.
- Download Desktop.GitHub, or use the command line CLI to synchronize your project.
- Read the slides (Ru) Version Control System.
- Send your login name to your group coordinator to join /github.com/intsystems.
Programming
- Install Python Anaconda,
- install PyCharm or Visual Studio,
- try Google Colab.
- 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
- Look through the list of projects (Spring 2025).
- Find public information about the experts and consultants.
- Select your projects during the group discussion.
- Wait for confirmation from the coordinator of your student group.
- Politely write your consultant and discuss your project.
Homework
- Fill in the questionnaire of Week 1: Imagine and plan a project
- Run all steps of Section Select your project
- Rigorously follow all the steps of Section Set the toolbox
- Write your coordinator and get access to the GitHub
- Open your notebook in the LinkReview format to gather your notes, thoughts, and references about your project.
References to catch up
- Bishop C.P. Pattern recognition and machine learning, Berlin: Springer, 2008 or see the version 2024 on Deep Learning
- MackKay D. Information Theory, Pattern Recognition and Neural Networks, Inference.org.uk, 2009
- A Brief Introduction to Machine Learning for Engineers by Osvaldo Simeone, 2017-2018
- Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz, Shai Ben-David, 2014
- Mathematics for Machine Learning by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong
- Mathematics for Physicists: Introductory Concepts and Methods by Alexander Altland & Jan von Delf
- Python notes for professionals by GoalKicker.com Free Programming Books.
- Computer Mathematics by D.J. Cooke and H.E. Bez, 1984 (Ru Кук, Бейз)