Thanks for raising the question! There is this recent text co-authored by @yoninazarathy and made available in draft form here: https://people.smp.uq.edu.au/YoniNazarathy/julia-stats/StatisticsWithJulia.pdf
(caught that in this post: Multivariate Normal Distribution - #8 by yoninazarathy)
This seems relevant to your question in particular:
9 Machine Learning Basics - DRAFT . . . . . . . . . . . . . . . 311
9.1 Training, Validation and Testing . . . . . . . . . . . . . 311
9.2 Bias, Variance and Regularization . . . . . . . . . . . . . 312
9.3 Supervised Learning Methods . . . . . . . . . . . . . . . . 315
9.4 Unsupervised Learning Methods . . . . . . . . . . . . . . 324
9.5 Reinforcement Learning and MDP . . . . . . . . . . . . . . 333
9.6 A Taste of Generational Adversarial Networks . . . . . . . 340
It’s a beautifully typeset text, and you can copy the Julia examples right out of the pdf and generate the same output and plots to validate.
There’s another good stats ref to pass along … thinking, or unthinking, let me dig it up…