Machine learner sentiment classifier, with ability to negate words, with english and german
With this package, you can generate predictions of machine learning models trained with YDF in browser and with NodeJS.
Unique machine (desktop) id (no admin privileges required).
Dispatcher contains a Softmax learner initially used for auto-active-learning down-sampling and a ML confusion-matrix evaluator on intent classification models.
Easy as cake e-mail sending from your Node.js applications
DreamCoder-style hierarchical abstraction and library learning for MUSUBIX
Learning-mode tutoring, review loops, and definition overlays for pi.
State management made super simple
Best-effort discovery of the machine's default gateway and local network IP exclusively with UDP sockets.
CoorpAcademy web slide-player
A conversational AI-driven telecom multi-agent system for managing call balances, push notifications, marketing, targeting, and sales.
State machine utilities for the Reach UI library.
Core logic for the checkbox widget implemented as a state machine
mykademy learner dashboard
Explode async and generator functions into a state machine.
Build functions in standardized containers.
A visual builder for your Slice Models with all the tools you need to generate data models and mock CMS content locally.
A finite state machine library
Creates a consistent, implementation-agnostic hash from a given raw machine ID resolution function. Designed to be used by MongoDB Tools.
XState for finite state machines
Native retrieval of a unique desktop machine ID without admin privileges or child processes. Faster and more reliable alternative to node-machine-id.
A React component that replaces the learner-dashboard's course list with one that supports archiving courses. Wired into the `org.openedx.frontend.learner_dashboard.course_list.v1` plugin slot. Reads each course's archive state from a filter-injected slot
JSON for Humans
A finite state machine iterator for JavaScript
Training loop, metrics, and callbacks for ferrotorch
MiniBoosts: A collection of boosting algorithms written in Rust 🦀
Zero-config nonparametric supervised learning — KNN with auto-tuned K, metric learning, and VP-tree indexing
High-performance Gradient Boosted Decision Tree engine for large-scale tabular data
Machine learning framework with spatial modeling, conformal prediction, and gradient boosting competitive with C++
Natural Gradient Boosting for Probabilistic Prediction - A Rust implementation of NGBoost
Multi-output regression and classification
PyTorch in Rust — deep learning framework built on ferray
A small, pure-Rust gradient boosting library (GBDT, binary classification, CPU only).
Multiclass classification strategies
AI-powered shape induction and data repair suggestions for SHACL validation
Streaming ML in Rust -- gradient boosted trees, neural architectures (TTT/KAN/MoE/Mamba/SNN), AutoML, kernel methods, and composable pipelines
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