https://www.youtube.com/watch?v=jC2pXSxqYLg вводное видео вот этого курса https://juliaacademy.com/p/computational-modeling-in-julia-with-applications-to-the-covid-19-pandemic/

What should I read in order to / Что мне почитать, чтобы:


1. Understand basics of Julia / Понять основы языка Julia ?

1.1 ThinkJulia: https://benlauwens.github.io/ThinkJulia.jl/latest/book.html
1.2 QuantEcon parts: https://julia.quantecon.org/
1.3 Zero2Hero Julia: https://www.youtube.com/watch?v=Fi7Pf2NveH0
1.4 Julia wiki: https://en.wikibooks.org/wiki/Introducing_Julia
1.5 From zero to Julia: https://techytok.com/from-zero-to-julia/
1.6 Jane Herriman intro to Julia: https://www.youtube.com/watch?v=8h8rQyEpiZA
1.7  Introduction to Computational Thinking with Julia, with applications to
modelling the COVID-19 pandemic: https://github.com/mitmath/6S083
1.8 Julia as CLI calculator (concrete example of workflow): https://krasjet.com/rnd.wlk/julia/


2. Understand Julia more deeply / Лучше понять некоторые тонкие аспекты Julia?

2.1 Chris Rachauckas tutorial: https://ucidatascienceinitiative.github.io/IntroToJulia/
2.2 Tom Kwong. Hands-on Design Patterns and Best Practices with Julia.
2.3 Malcolm Sherrington. Mastering Julia.
2.4 Julia workshop 2019 (Finland): https://github.com/crstnbr/JuliaOulu20
2.5 D.P.Sanders workshop: https://github.com/dpsanders/hands_on_julia
2.6 Metaprogramming workshop: https://youtu.be/SeqAQHKLNj4
2.7 Parallel computing workshop: https://github.com/mbauman/ParallelWorkshop2019
2.8 Curated list of julia packages for all branches: https://github.com/svaksha/Julia.jl/blob/master/AI.md


3. Learn some applications to specific branches of mathematics / Узнать больше о
приложениях к некоторым областям математики?

3.1 Linear algebra / Линейная алгебра:

3.1.1 Introduction to applied linear algebra: vectors, matrices and least
squares http://vmls-book.stanford.edu/
3.1.2 Folkmar Bornemann: Numerical Linear Algebra. A Concise Introduction  with MATLAB and Julia
3.1.3 MODERN APPLICATIONS OF NUMERICAL LINEAR ALGEBRA METHODS: https://github.com/ivanslapnicar/GIAN-Applied-NLA-Course

3.2 Differential equations, dynamical systems / Дифуры и динамич. системы:

3.2.1 DynamicalSystems.jl tutorial: https://www.youtube.com/watch?v=13hqE_1a158
3.2.2 DifferentialEquations tutorial: https://www.youtube.com/watch?v=13hqE_1a158
3.2.2 Partial Differential Equations tutorial: https://www.youtube.com/watch?v=13hqE_1a158

3.3 Optimization / Оптимизация:

3.3.1 Kochenderfer, Wheeler : Algorithms for Optimization
3.3.2 Kwong: Julia Programming for Operations Research, 2nd Edition

3.4 Data science / Наука о данных:

3.4.1 Data science workshop: https://youtu.be/SLE0vz85Rqo
3.4.2 Queryverse workshop: https://www.youtube.com/watch?v=OFPNph-WxLM

3.5 Statistics, bayesian, etc / Статистика, байесовский подход и др.:

3.5.1 Statistics with julia: https://github.com/h-Klok/StatsWithJuliaBook
3.5.2 Turing language tutorials: https://turing.ml/dev/tutorials/
3.5.3 Statistical rethinking in Julia: https://github.com/StatisticalRethinkingJulia/StatisticalRethinking.jl

3.6 Calculus, symbolic computations, ... / Анализ, символьные вычисления:

3.6.1 Calculus with julia : http://calculuswithjulia.github.io/

3.7 Deep learning (глубокое обучение):

3.7.1 Flux model ZOO : https://github.com/FluxML/model-zoo




4. Ecosystem, packages, etc / Экосистема, пакеты и иное:

4.1 How to write a package (Rackauckas) https://youtu.be/QVmU29rCjaA
4.2 How to install https://youtu.be/oyx8M1yoboY