Posts tagged #scikit-learn

Jun 30, 2026 · 6 min

sklears 0.1.2 Released — Preprocessing Completions, SciRS2 0.5.1, and AVX2 Quicksort

sklears 0.1.2 brings 12 real preprocessing implementations (no more stubs), SciRS2 0.5.1 upgrade, AVX2 quicksort in sklears-simd, advanced categorical imputers, and a full benchmarking regression-detection subsystem — 12,242 tests across 36 crates, >99% scikit-learn API coverage held.

releasesklearsmachine-learning

Apr 27, 2026 · 5 min

sklears 0.1.1 Released — Correctness Fixes for HDBSCAN, Streaming, and Pipelines

sklears 0.1.1 is a correctness patch for pure-Rust scikit-learn: HDBSCAN cluster-persistence fix, streaming scaler/imputer Default cleanups, a pipeline lifetime fix, and serialization fixes — 11,586+ tests across 36 crates, >99% scikit-learn API coverage held.

releasesklearsmachine-learning

Mar 20, 2026 · 6 min

sklears 0.1.0 Released — Pure Rust scikit-learn with >99% API Coverage

The first stable release of sklears: a pure-Rust scikit-learn alternative spanning 36 crates with >99% API coverage, type-safe Untrained→Trained state machines, and a SciRS2 foundation. No Python runtime, no GIL, no C or Fortran.

releasesklearsmachine-learning

Mar 5, 2026 · 8 min

SciRS2 0.3.0 Released — The Largest Feature Expansion Yet: Modern Deep Learning, Advanced Statistics, and Signal Processing in Pure Rust

SciRS2 is a pure-Rust SciPy/NumPy/scikit-learn replacement, and 0.3.0 is the biggest release yet — transformers, GNNs, diffusion, MoE/RLHF, Gaussian processes, MCMC, survival analysis, radar/compressed sensing, LOBPCG/AMG, plus new Julia and Python bindings. 19,644 tests, ~2.59M lines of Rust. No C, no Fortran.

releasescirs2scientific-computing