Search Results for "support vector machine" - Page 2
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Showing 73 open source projects for "support vector machine"
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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... -
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SIA
AI framework to autonomously improve the performance of any AI system
SIA is a self-improving AI framework designed to improve the performance of models or agents on benchmark tasks. It uses an iterative loop where a meta-agent creates or updates a task-specific target agent, while a feedback agent studies results and proposes improvements. The framework can refine both the harness around the task and the agent implementation itself. It is aimed at research and experimentation across tasks such as machine learning benchmarks, legal classification, code... -
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ergo
Framework for creating microservices using technologies of Erlang/OTP
Technologies and design patterns of Erlang/OTP have been proven over the years. Now in Golang. Up to x5 times faster than original Erlang/OTP in terms of network messaging. The easiest way to create an OTP-designed application in Golang. The goal of this project is to leverage Erlang/OTP experience with Golang performance. The ideal framework for creating complex and distributed solutions (machine learning, data processing pipeline, etc.) being simple and reliable. You don't have to reinvent... -
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Fuzzy machine learning framework
A library and a GUI front-end for fuzzy machine learning
Fuzzy machine learning framework is a library and a GUI front-end for machine learning using intuitionistic fuzzy data. The approach is based on the intuitionistic fuzzy sets and the possibility theory. Further characteristics are fuzzy features and classes; numeric, enumeration features and features based on linguistic variables; user-defined features; derived and evaluated features; classifiers as features for building hierarchical systems; automatic refinement in case of dependent features; incremental learning; fuzzy control language support; object-oriented software design with extensible objects and automatic garbage collection; generic data base support through ODBC or SQLite; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use. -
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MegEngine
Easy-to-use deep learning framework with 3 key features
MegEngine is a fast, scalable and easy-to-use deep learning framework with 3 key features. You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR... -
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Iris Web Framework
The fastest community-driven web framework for Go
Iris is a fast, full-featured and futuristic web framework written in Go. It is by far the fastest HTTP/2 web framework ever crafted, is highly efficient yet simple. Iris provides a beautifully expressive and easy-to-use foundation for your next website, API or distributed app. Iris comes packed with Webassembly, Automatic HTTPS with Public Domain, MVC, Sessions, Caching, Versioning API, Problem API, Websocket, Dependency Injection and more. It is also fully-compatible with the standard... -
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN... -
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towhee
Framework that is dedicated to making neural data processing
...Towhee provides out-of-the-box integration with your favorite libraries, tools, and frameworks, making development quick and easy. Towhee includes a pythonic method-chaining API for describing custom data processing pipelines. We also support schemas, making processing unstructured data as easy as handling tabular data. -
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BEVFormer
Implementation of BEVFormer, a camera-only framework
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV... -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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OpenPrompt
An Open-Source Framework for Prompt-Learning
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks, which modifies the input text with a textual template and directly uses PLMs to conduct pre-trained tasks. OpenPrompt is a library built upon PyTorch and provides a standard, flexible and extensible framework to deploy the prompt-learning pipeline. OpenPrompt supports loading PLMs directly from huggingface transformers. In the future, we will also support PLMs implemented by other... -
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Sentinel Golang
Sentinel Go enables reliability and resiliency for Go microservices
As distributed systems become increasingly popular, the reliability between services is becoming more important than ever before. Sentinel takes "flow" as the breakthrough point and works on multiple fields including flow control, circuit breaking and system adaptive protection, to guarantee the reliability and resiliency of microservices. Rich applicable scenarios: Sentinel has been wildly used in Alibaba, and has covered almost all the core-scenarios in Double-11 (11.11) Shopping Festivals... -
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Hyperledger Burrow
A permissioned Ethereum smart-contract blockchain node
Hyperledger Burrow is a permissioned Ethereum smart-contract blockchain node. It executes Ethereum EVM and WASM smart contract code (usually written in Solidity) on a permissioned virtual machine. Burrow provides transaction finality and high transaction throughput on a proof-of-stake Tendermint consensus engine. Burrow is a fully-fledged blockchain node and smart contract execution engine -- a distributed database that executes code. Burrow runs Ethereum Virtual Machine (EVM) and Web... -
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GoSpider
Gospider - Fast web spider written in Go
...Parse robots.txt. Generate and verify link from JavaScript files. Link Finder. Find AWS-S3 from response source. Find subdomains from the response source. Get URLs from Wayback Machine, Common Crawl, Virus Total, Alien Vault. Format output easy to Grep. Support Burp input. Crawl multiple sites in parallel. -
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TNN
Uniform deep learning inference framework for mobile
TNN, a high-performance, lightweight neural network inference framework open sourced by Tencent Youtu Lab. It also has many outstanding advantages such as cross-platform, high performance, model compression, and code tailoring. The TNN framework further strengthens the support and performance optimization of mobile devices on the basis of the original Rapidnet and ncnn frameworks. At the same time, it refers to the high performance and good scalability characteristics of the industry's... -
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RESTful API Node Server Boilerplate
A boilerplate for building production-ready RESTful APIs using Node.js
A boilerplate/starter project for quickly building RESTful APIs using Node.js, Express, and Mongoose. By running a single command, you will get a production-ready Node.js app installed and fully configured on your machine. The app comes with many built-in features, such as authentication using JWT, request validation, unit and integration tests, continuous integration, docker support, API documentation, pagination, etc. The app has a utility ApiError class to which you can attach a response code and a message, and then throw it from anywhere (catchAsync will catch it). ... -
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Gluon CV Toolkit
Gluon CV Toolkit
GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection,... -
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Kore
Scalable and secure web application framework
Kore is a web application platform for writing scalable, concurrent web-based processes in C or Python. It is built with a "secure by default" approach. It is fully privileged separated while using strong security features at the operating system level such as second, pledge, unveil, and more. Today Kore is used in a variety of applications ranging from high assurance cryptographic military devices, machine-learning stacks and even in the aerospace industry. From embedded platforms all the... -
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Keystone Engine
Keystone assembler framework: Core (Arm, Arm64, Hexagon, Mips, etc.)
Keystone is a lightweight multi-platform, multi-architecture assembler framework. Multi-architecture, with support for Arm, Arm64 (AArch64/Armv8), Ethereum Virtual Machine, Hexagon, Mips, PowerPC, Sparc, SystemZ, & X86 (include 16/32/64bit). Clean/simple/lightweight/intuitive architecture-neutral API. Implemented in C/C++ languages, with bindings for Java, Masm, Visual Basic, C#, PowerShell, Perl, Python, NodeJS, Ruby, Go, Rust, Haskell & OCaml available. -
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Multrin
Organize apps windows in tabs like in abandoned Windows Sets and more
Multrin is a cross-platform app built on Electron that lets you to organize apps in tabs by simply dropping them onto Multrin. It aims to greatly improve your productivity and organization. Multrin works currently only on Windows and macOS. Support for Linux coming soon. Before running Multrin in development mode, please ensure you have Node.js installed on your machine. When running on Windows, make sure you have build tools installed. You can install them by running as an administrator. -
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Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
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abu
Abu quantitative trading system (stocks, options, futures, bitcoin)
Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models,... -
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RKH - State Machine Framework
State machine framework for reactive embedded systems
RKH is a generic, flexible, modular, highly portable, ANSI-C compliant, and open-source development tool for implementing hierarchical state machines based on modern state machine concepts. This modern techniques are used to give an abstract description of the dynamic behavior of a system in a substantial manner. The RKH not implements neither entire UML specs. nor entire Statechart specs. Instead, the RKH intention is to support just enough basic concepts of that powerful tools to facilitate the reactive-system modeling holding a solid, and efficient implementation. ... -
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GPUImage 2
Framework for GPU-accelerated video and image processing
...The original GPUImage framework was written in Objective-C and targeted Mac and iOS, but this latest version is written entirely in Swift and can also target Linux and future platforms that support Swift code. The objective of the framework is to make it as easy as possible to set up and perform realtime video processing or machine vision against image or video sources. By relying on the GPU to run these operations, performance improvements of 100X or more over CPU-bound code can be realized. This is particularly noticeable in mobile or embedded devices. ...
