Search Results for "state machine c"
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Showing 2750 open source projects for "state machine c"
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The Algorithms - C++ #
Collection of various algorithms in mathematics, machine learning
...Within the C++ repository, contributors implement algorithms across a wide range of fields including sorting, graph theory, number theory, machine learning, cryptography, and data structures. Each implementation is designed to be readable and well documented so that learners can understand the logic and structure behind each algorithm. The repository functions both as a study resource and as a reference library for developers who want examples of algorithm implementations in C++. ... -
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Candle
GRBL controller application with G-Code visualizer written in Qt
GRBL controller application with G-Code visualizer written in Qt. -
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C/C++ for Visual Studio Code
Repository for the Microsoft C/C++ extension for VS Code
The C/C++ extension adds language support for C/C++ to Visual Studio Code, including features such as IntelliSense and debugging. C/C++ support for Visual Studio Code is provided by a Microsoft C/C++ extension to enable cross-platform C and C++ development on Windows, Linux, and macOS. C++ is a compiled language meaning your program's source code must be translated (compiled) before it can be run on your computer. VS Code is first and foremost an editor, and relies on command-line tools to... -
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Django friendly finite state machine
Django friendly finite state machine support
Django-fsm adds simple declarative state management for Django models. If you need parallel task execution, view, and background task code reuse over different flows - check my new project Django-view flow. Instead of adding a state field to a Django model and managing its values by hand, you use FSMField and mark model methods with the transition decorator. These methods could contain side effects of the state change. You may also take a look at the Django-fsm-admin project containing a... -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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FSM for Go
Finite State Machine for Go
FSM is a finite state machine for Go. It is heavily based on two FSM implementations. Javascript Finite State Machine, and Fysom for Python. Visualize outputs a visualization of a FSM in Graphviz format. VisualizeForMermaidWithGraphType outputs a visualization of a FSM in Mermaid format as specified by the graphType. VisualizeWithType outputs a visualization of a FSM in the desired format. -
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XState
State machines and statecharts for the modern web
JavaScript and TypeScript finite state machines and statecharts for the modern web. Statecharts are a formalism for modeling stateful, reactive systems. This is useful for declaratively describing the behavior of your application, from the individual components to the overall application logic. XState is a library for creating, interpreting, and executing finite state machines and statecharts, as well as managing invocations of those machines as actors. The following fundamental computer... -
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WorkflowEngine.NET
WorkflowEngine.NET - component that adds workflow in your application
WorkflowEngine.NET is a flexible workflow engine for .NET applications that supports visual process design and dynamic execution of business logic. It enables developers to model complex workflows with conditions, branching, and state transitions. The engine is highly customizable and can be embedded into any .NET project to automate tasks and decision-making. -
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Oumi
Everything you need to build state-of-the-art foundation models
Oumi is an open-source framework that provides everything needed to build state-of-the-art foundation models, end-to-end. It aims to simplify the development of large-scale machine-learning models. -
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Spring Statemachine
Framework for application developers to use state machine concepts
The Spring Statemachine project aims to provide a common infrastructure to work with state machine concepts in Spring applications. It is advised to check the actual state of this project by referring to the latest releases found on the Spring Statemachine Project Page. The git repo default branch may be relatively unstable when new features are added to the source code. Spring Statemachine uses a Gradle-based build system. -
Add Two Lines of Code. Get Full APM.Works out of the box for Rails, Django, Express, Phoenix, and more. Monitoring exceptions and performance in no time.
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InterpretML
Fit interpretable models. Explain blackbox machine learning
In the beginning, machines learned in darkness, and data scientists struggled in the void to explain them. InterpretML is an open-source package that incorporates state-of-the-art machine-learning interpretability techniques under one roof. With this package, you can train interpretable glass box models and explain black box systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. -
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Open Source Routing Machine
Open Source Routing Machine - C++ backend
High-performance routing engine written in C++14 designed to run on OpenStreetMap data. There are several services available via HTTP API, C++ library interface and NodeJs wrapper. Nearest, snaps coordinates to the street network and returns the nearest matches. Route finds the fastest route between coordinates. Table computes the duration or distances of the fastest route between all pairs of supplied coordinates. Match snaps noisy GPS traces to the road network in the most plausible way.... -
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flair
A very simple framework for state-of-the-art NLP
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. A powerful NLP library. Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), sentiment analysis, part-of-speech tagging (PoS), special support for biomedical texts, sense disambiguation and classification, with support for a rapidly growing number of languages. A text embedding library. Flair has... -
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deepface
A Lightweight Face Recognition and Facial Attribute Analysis
DeepFace is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid face recognition framework wrapping state-of-the-art models: VGG-Face, FaceNet, OpenFace, DeepFace, DeepID, ArcFace, Dlib, SFace and GhostFaceNet. Experiments show that human beings have 97.53% accuracy on facial recognition tasks whereas those models already reached and passed that accuracy level. -
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Vowpal Wabbit
Machine learning system which pushes the frontier of machine learning
Vowpal Wabbit is a machine learning system that pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning. There is a specific focus on reinforcement learning with several contextual bandit algorithms implemented and the online nature lending to the problem well. -
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StemRoller
Isolate vocals, drums, bass, and other instrumental stems from songs
StemRoller is the first free app that enables you to separate vocal and instrumental stems from any song with a single click! StemRoller uses Facebook's state-of-the-art Demucs algorithm for demixing songs and integrates search results from YouTube. Simply type the name/artist of any song into the search bar and click the Split button that appears in the results! You'll need to wait several minutes for splitting to complete. Once stems have been extracted, you'll see an Open button next to... -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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LightGBM
Gradient boosting framework based on decision tree algorithms
LightGBM or Light Gradient Boosting Machine is a high-performance, open source gradient boosting framework based on decision tree algorithms. Compared to other boosting frameworks, LightGBM offers several advantages in terms of speed, efficiency and accuracy. Parallel experiments have shown that LightGBM can attain linear speed-up through multiple machines for training in specific settings, all while consuming less memory. LightGBM supports parallel and GPU learning, and can handle... -
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Transformers
State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX
Hugging Face Transformers provides APIs and tools to easily download and train state-of-the-art pre-trained models. Using pre-trained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a model from scratch. These models support common tasks in different modalities. Text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages. Images, for tasks... -
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Quantum++
Modern C++ quantum computing library
...The main design factors taken in consideration were ease of use, high portability, and high performance. The library's simulation capabilities are only restricted by the amount of available physical memory. On a typical machine (Intel i5 8Gb RAM) Quantum++ can successfully simulate the evolution of 25 qubits in a pure state or of 12 qubits in a mixed state reasonably fast. -
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? -
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zag
Finite state machines for building accessible design systems and UI
A collection of framework-agnostic UI components patterns like an accordion, menu, and dialog that can be used to build design systems for React, Vue, and Solid.js. Simple, resilient component logic. Write component logic once and use it anywhere. Built-in adapters that connect machine output to DOM semantics in a WAI-ARIA-compliant way. Component logic is largely JavaScript code and can be consumed in any JS framework. Zag machine APIs are completely headless and unstyled. Use your favorite styling solution and get it matching your design system. Finite state machines for building accessible design systems and UI components. ... -
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ONNX Runtime
ONNX Runtime: cross-platform, high performance ML inferencing
ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators... -
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Triton Inference Server
The Triton Inference Server provides an optimized cloud
...Provides Backend API that allows adding custom backends and pre/post-processing operations. Model pipelines using Ensembling or Business Logic Scripting (BLS). HTTP/REST and GRPC inference protocols based on the community-developed KServe protocol. A C API and Java API allow Triton to link directly into your application for edge and other in-process use cases. -
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The Acton programming language
The Acton Programming Language
...Acton programs, and the actor model, work well from simple script-style applications on a single machine up to large distributed systems across a Data Center. Run at your scale. -
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EconML
Python Package for ML-Based Heterogeneous Treatment Effects Estimation
EconML is a Python package for estimating heterogeneous treatment effects from observational data via machine learning. This package was designed and built as part of the ALICE project at Microsoft Research with the goal of combining state-of-the-art machine learning techniques with econometrics to bring automation to complex causal inference problems. One of the biggest promises of machine learning is to automate decision-making in a multitude of domains. ...
