Difference between revisions of "Week 1"
From m1p.org
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# Download [http://jmlda.org/papers/doc/jmlda-guides.zip the paper template, ZIP] and compile it. | # Download [http://jmlda.org/papers/doc/jmlda-guides.zip the paper template, ZIP] and compile it. | ||
# '''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/rec/journals/hisas/DorinKGS24.html?view=bibtex An example of a bibliographic record]. |
#* [https://docs.google.com/document/d/10JgJMieX13R5vlrCfJPrMqU9Rsd4c4JzaGytU8rWFE4/edit?usp=sharing An example of draft review LinkReview]. | #* [https://docs.google.com/document/d/10JgJMieX13R5vlrCfJPrMqU9Rsd4c4JzaGytU8rWFE4/edit?usp=sharing An example of draft review LinkReview]. | ||
#* [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]. |
Revision as of 16:52, 21 February 2025
The goal of this week is to set up your tools, and to select your project.
Set the toolbox
- Editors. Install LaTeX: MikTeX for Windows, TeX Live for Linux, and Mac OS. Sign up V2 OverLeaf ShareLaTeX.
- Install the editor TeXnic Center or its alternative WinEdt for Windows, TeXworks for Linux, and TeXmakerfor Mac OS.
- Read Львовский С.М. Набор и верстка в системе LaTeX (Ru).
- Read LaTeX on MachineLearning (Ru).
- Useful: Wikibooks LaTeX, К.В.Воронцов. LaTeX2e в примерах (Ru).
- Note Мильчин А.Э. Чельцова Л.К. Справочник издателя и автора (Ru).
- Download the paper template, ZIP and compile it.
- References. Read BibTeX.
- Install bibliographic collection software JabRef (can be postponed).
- 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.
- Introduction to GitHub.
- The first steps in GitHub.
- Download a shell: Desktop.GitHub, or use a command line to synchronize your project.
- Sign up MachineLearning.ru. Send your login name to your coordinator (or to mlalgorithms [at] gmail [dot] com; to find the coordinator).
- Programming. Install Python Anaconda, PyCharm (alternative Visual Studio), Notebook online Google.Colab.
- Development for ML: PyTorch
- Style formatting: Codestyle pep8
- Add. As alternative install and try Matlab (check of your university provides a free version), (alternative Octave), R-project, Wolfram Mathematica.
- 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:
- 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 responsible coordinator of your student group
- Put confirmed topics Group table (Spring 2025).
- Politely write your consultant and discuss your project.
Resources
Obsoleted
References to catch up
- 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.
- Лагутин М.Б. Наглядная математическая статистика, М.: Бином, 2009. См. также вырезку (Ru)
- Bishop C.P. Pattern recognition and machine learning, Berlin: Springer, 2008
- MackKay D. Information Theory, Pattern Recognition and Neural Networks, Inference.org.uk, 2009
Homework
- Fill the questionnaire week m1 – Imagine and plan a project
- Watch video
- Watch the video Риски и результаты в машинном обучении Risics and results in machine learning
- Rigorously follow all the steps of section Set the toolbox
- Check if you can briefly explain what is
- statistical hypothesis
- statistical inference,
- conditional and joint distributions,
- likelihood function,
- algebraic structure
- Watch the video Моя первая научная статья 0 My first scientific paper, week 0