Please see https://github.com/JuliaStats/MLBase.jl/blob/master/NEWS.md for recent updates.
Also the documentation is moved from Readme to a Sphinx doc <http://mlbasejl.readthedocs.org/en/latest/> Now we already have quite a few packages for various machine learning tasks: MLBase.jl <https://github.com/JuliaStats/MLBase.jl>: data preprocessing, performance evaluation, cross validation, model tuning, etc Distance.jl <https://github.com/JuliaStats/Distance.jl>: metric/distance computation (including batch & pairwise computation) MultivariateStats.jl <https://github.com/JuliaStats/MultivariateStats.jl>: multivariate analysis, ridge regression, dimensionality reduction Clustering.jl <https://github.com/JuliaStats/Clustering.jl>: K-means, K-medoids, Affinity propagation NMF.jl <https://github.com/JuliaStats/NMF.jl>: Nonnegative matrix factorization In addition, we have a bunch of other packages for Regression, GLM, SVM, etc. We are now beginning to unite the efforts in this domain (see the discussion <https://github.com/JuliaStats/Roadmap.jl/issues/14> here). We have been making steady progress, and I believe that we will have a great machine learning ecosystem, one that is comparable or even superior to scikit.learn in not too long future. Cheers, Dahua
