Comprehensive, type-safe framework unifying tensors, DataFrames, neural networks, and classical ML into a single modular package.
npm install deepboxNode ≥ 24.131import { tensor, add, parameter } from "deepbox/ndarray"2import { DataFrame } from "deepbox/dataframe"3import { LinearRegression } from "deepbox/ml"45// Tensor operations6const a = tensor([[1, 2], [3, 4]])7const b = tensor([[5, 6], [7, 8]])8const c = a.add(b) // [[6, 8], [10, 12]]910// Automatic differentiation11const x = parameter([2, 3])12const y = x.mul(x).sum()13y.backward() // x.grad -> tensor([4, 6])1415// DataFrames16const df = new DataFrame({17 name: ["Alice", "Bob"],18 score: [85, 90]19})2021// Machine learning22const model = new LinearRegression()23model.fit(XTrain, yTrain)From tensor operations to model training — everything in one package.
Dense and sparse tensors with autograd, FFT, einsum, signal processing, and rich dtype support.
GradTensor with full backward pass support for neural network training.
Tabular workflows with accessors, window ops, IO, styling, and plotting integration.
Modules, containers, conv/recurrent/transformer layers, losses, trainer, and initialization.
Linear, tree, ensemble, SVM, neighbors, anomaly, calibration, and model-selection APIs.
Distributions, KDE, hypothesis tests, confidence intervals, and evaluation metrics.
deepbox/coreRuntime types, validation, config, backends, serialization, worker poolsdeepbox/ndarrayDense and sparse tensors, autograd, FFT, einsum, signal and numerical opsdeepbox/linalgSVD, QR, LU, Cholesky, eigendecomposition, solvers, normsdeepbox/dataframeDataFrame, Series, accessors, window ops, IO, styling, plottingdeepbox/statsDescriptive stats, distributions, KDE, tests, confidence, powerdeepbox/mlLinear, trees, ensembles, SVM, neighbors, clustering, pipelines, selectiondeepbox/nnModules, conv/recurrent/transformer layers, losses, trainer, initializationdeepbox/optimSGD, Adam-family, LAMB/LARS/LBFGS, and scheduler policiesdeepbox/metricsClassification, regression, clustering, ranking, and pairwise metricsdeepbox/preprocessScalers, encoders, imputers, feature engineering, text, CV splitsdeepbox/randomSeeded generation, Generator, distributions, and sampling utilitiesdeepbox/datasetsBuilt-in loaders, remote helpers, Kaggle, generators, and DataLoaderdeepbox/plotFigure API, diagnostics, animation, interactive, SVG/PNG/PDF output