Getting Started in Julia

Resources for

Beginners

(If you are new to programming)

• Julia Installation & Setup (Part of Introduction to Julia Machine Learning book)

Intermediate Programmers

(If you are proficient in Python/MATLAB/R)

• [Cheatsheet] Comparison of basic statistics/linear algebra in Python/Julia/MATLAB

• [Official Documentation] Julia’s noteworthy differences from other languages

• [MIT Opencourseware] Introduction to Computational Thinking

• [Online Book & Lectures] Introduction to Parallel Computing and Scientific Machine Learning

Advanced Programmers

(If you have developed APIs and software in other languages)

• [Book] Kwong, T. (2020). Hands-On Design Patterns and Best Practices with Julia: Proven solutions to common problems in software design for Julia 1. x. Packt Publishing Ltd.

• [Book] Balbaert, I., Sengupta, A., & Sherrington, M. (2016). Julia: High Performance Programming. Packt Publishing Ltd.

Packages for Computational Modeling

You can search through the list of all registered julia package here.

• List of packages for basic modeling (Linear Models, Clustering, Hypothesis Testing, etc.)
• Mainstream Machine Learning
  • ScikitLearn.jl
    • [Learning Resource] Sudheesh, A. (2022). Introduction to Julia Machine Learning
  • MLJ.jl
• Neural Networks
  • Flux.jl
• List of packages for all sorts of optimization
• Differential Equations based Modeling
  • DynamicalSystems.jl
  • DiffEq.jl
• Bayesian Inference & Probabilistic Programming
  • Turing.jl
• Probablistic Graphical Models
  • BayesNet.jl
  • JunctionTrees.jl
  • Markov Decision Process POMDPs.jl