Julia for Data Science - Video 7: Regression, by Dr. Huda Nassar (for JuliaAcademy.com)
Introduction to Programming in Julia Part 2 of 4
MendelIHT.jl: Generalized Linear Models for High Dimensional Genetics (GWAS) Data | JuliaCon 2019
Introduction to Programming in Julia Part 3 of 4
Fitting Statistical Models in Julia Douglas Bates | JuliaCon 2014
Hands on with Julia | Bayesian Logistic Regression with Horse Shoe Prior | Genetic Data Analysis
[02x04] Statistics Fundamentals; StatsBase HypothesisTests | 4/13 Julia Analysis for Beginners
RegressionFormulae.jl: Familiar `@formula` Syntax for... | P. Alday, D. Kleinschmidt | JuliaCon 2022
Full Guide
Data is compiled from public records and verified media reports.
Last Updated: September 29, 2026
Final Thoughts
For 2026, 4 Julia Regression remains one of the most talked-about information profiles. Check back for the latest updates.
Disclaimer: Disclaimer: All information is compiled from publicly available data, media reports, and analysis. Actual details may vary.
Summary
In this tutorial, you'll get in introduction to Supervised Learning, which is one of the main categories of Machine Learning. This talk was presented as part of JuliaCon 2021. Abstract: Visit julialang.org/ to download Registration for this years Virtual JuliaCon 2020 is available now (for free): juliacon.org/2020/tickets/. Join the course at: ... Speaker: Benjamin Chu GWAS data are extremely high dimensional, large, dense, and typically contains rare and correlated ... Presented by Douglas Bates at JuliaCon 2014. In this hand on, we implement the Bayesian Logistic StatsModels.jl provides the ` mini-language for conveniently specifying table-to-matrix transformations for statistical ...