Show HN: 8M algorithms in 56 KB – Rust/WASM library for JavaScript (github.com)

The newly launched micro-ml library offers a compact and efficient solution for performing machine learning tasks directly in JavaScript applications, requiring only ~56KB when gzipped. This library, built on WebAssembly (WASM), packs an impressive suite of 8 machine learning algorithms, regression techniques, and data smoothing functions that can execute in sub-millisecond response times. For developers needing straightforward predictive analytics, such as sales forecasting or trend analysis, micro-ml eliminates the need for heavier libraries like TensorFlow.js, which can exceed 500KB. This innovation is particularly significant for the AI/ML community as it democratizes access to machine learning capabilities by enabling lightweight implementations that are easy to integrate into web applications. The library's performance metrics—such as linear regression completing in just 0.9ms for 100,000 points—underscore its potential for real-time applications. Tools like trend forecasting, k-Means clustering, and logistic regression are now more accessible, allowing users to efficiently handle a variety of data analysis tasks without the overhead of larger frameworks, thus fostering a new wave of simpler, more responsive AI-driven applications.