Scholar is a comprehensive machine learning library for Elixir, built directly on Nx (Numerical Elixir). It provides a scikit-learn-inspired API with fit/predict/transform patterns across supervised learning (linear/logistic/ridge/Bayesian ridge regression, SVM, naive Bayes variants, discriminant analysis), unsupervised learning (KMeans, DBSCAN, OPTICS, HDBSCAN, GMM, hierarchical clustering, PCA, KernelPCA, t-SNE, MDS, TriMap), preprocessing (scalers, encoders, imputers), metrics (classification, regression, clustering, ranking, distance), model selection (cross-validation, grid search), optimization (BFGS, Nelder-Mead, Brent), interpolation, and numerical integration. The library is designed for JIT/GPU execution via EXLA, with all numerical kernels written as Nx defn functions and models as Nx.Container structs. The included Livebook notebooks are educational demos, not the primary artifact, so the repository is fundamentally an application/library rather than a data-research project.