Week 1
From m1p.org
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 the paper template and compile it. You need two files: .tex and .bib
- References. Read BibTeX.
- Install bibliographic collection software JabRef.
- 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.
- Download a shell: Desktop.GitHub, or use the command line CLI 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. See The Julia language and R project
- 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
- Video week 1
- Slides week 1.
- Slides for week 0.
- Video for week 0.
- Slides for week 1.
- Video for week 1.
- Short course description.
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)
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
- Join your inherited project repository (recommended) or create a new one (here will be the template)