Search Results for "full stack framework" - Page 7
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Showing 181 open source projects for "full stack framework"
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SGX-Full-OrderBook-Tick-Data-Trading
Providing the solutions for high-frequency trading (HFT) strategies
SGX-Full-OrderBook-Tick-Data-Trading-Strategy is an open-source research project focused on modeling high-frequency financial market behavior using machine learning techniques. The repository analyzes tick-level order book data from the Singapore Exchange and attempts to capture the dynamics of limit order book movements. By extracting features such as order depth ratios and price movement indicators, the system trains machine learning models to predict short-term market changes. Several... -
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Apache TVM
TVM Documentation in Chinese Simplified
...The project translates official TVM guides and organizes them into structured documentation that explains how to compile, optimize, and deploy deep learning models on heterogeneous hardware architectures. It also encourages community collaboration by inviting contributors to submit corrections, improvements, and additional translations as the TVM framework evolves. -
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Darknet YOLO
Real-Time Object Detection for Windows and Linux
This is YOLO-v3 and v2 for Windows and Linux. YOLO (You only look once) is a state-of-the-art, real-time object detection system of Darknet, an open source neural network framework in C. YOLO is extremely fast and accurate. It uses a single neural network to divide a full image into regions, and then predicts bounding boxes and probabilities for each region. This project is a fork of the original Darknet project. -
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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series forecasting framework. ... -
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Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. ... -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. -
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MaskFormer
Per-Pixel Classification is Not All You Need for Semantic Segmentation
MaskFormer is a unified framework for image segmentation developed by Facebook Research, designed to bridge the gap between semantic, instance, and panoptic segmentation within a single architecture. Unlike traditional segmentation pipelines that treat these tasks separately, MaskFormer reformulates segmentation as a mask classification problem, enabling a consistent and efficient approach across multiple segmentation domains. Built on top of Detectron2, it supports a wide range of datasets... -
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VoiceFixer
General Speech Restoration
VoiceFixer is a machine-learning framework for “speech restoration”: given a degraded or distorted audio recording — with noise, clipping, low sampling rate, reverberation, or other artifacts — it attempts to recover high-fidelity, clean speech. The architecture works in two stages: first an analysis stage that tries to extract “clean” intermediate features from the noisy audio (e.g. removing noise, denoising, dereverberation, upsampling), and then a neural vocoder-based synthesis stage that... -
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SparrowRecSys
A Deep Learning Recommender System
...SparrowRecSys supports a wide range of state-of-the-art recommendation algorithms, including models for click-through rate prediction and user behavior modeling that are widely used in advertising and content recommendation systems. The system is designed as a modular platform combining technologies such as Spark, TensorFlow, and web server components to represent the full lifecycle of recommendation pipelines. -
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neurojs
A JavaScript deep learning and reinforcement learning library
neurojs is a JavaScript framework designed to enable deep learning and reinforcement learning directly within web environments. The library provides a full machine learning framework implemented in JavaScript that can run inside browsers or Node.js environments. It focuses particularly on reinforcement learning algorithms, enabling developers to create intelligent agents that learn through interaction with simulated environments. -
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Astro Boy Chat Room
Atom chat room nestjs+vue full stack chat room
...A superset of JavaScript, its biggest advantage is to provide a type system and improve the readability and maintainability of the code. Real-time communication, websocket third-party library. Efficient and scalable Node.js server-side application framework, written based on TypeScript and combined with related concepts of OOP1, FP2, and FRP3. -
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Aide
The open source AI-native IDE
Aide is an AI software engineering assistant that provides conversational code generation, analysis, and refactoring directly within your IDE or through a local web interface. Built to act as a full-stack collaborator, it understands multi-file projects, detects dependency relationships, and can generate consistent updates across files and frameworks. It supports multiple backends—including OpenAI, Anthropic, and open-source models—and can route requests based on task type or latency requirements. Aide stores context efficiently, caching embeddings of codebases to accelerate reasoning and maintain memory across sessions. ... -
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End-to-End Negotiator
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
End-to-End Negotiator is a PyTorch-based research framework developed by Facebook AI Research to train neural agents capable of conducting strategic negotiations in natural language. The project implements the models presented in two key papers: “Deal or No Deal? End-to-End Learning for Negotiation Dialogues” and “Hierarchical Text Generation and Planning for Strategic Dialogue”. It enables agents to plan, reason, and communicate effectively to maximize outcomes in multi-turn negotiations... -
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jieba
Stuttering Chinese word segmentation
"Jaba" Chinese word segmentation, do the best Python Chinese word segmentation component. Four word segmentation modes are supported. Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable for word segmentation in search engines. The paddle mode uses the PaddlePaddle deep learning framework to train the sequence labeling (bidirectional GRU) network model to achieve word segmentation. ... -
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nGraph
nGraph has moved to OpenVINO
Frameworks using nGraph Compiler stack to execute workloads have shown up to 45X performance boost when compared to native framework implementations. We've also seen performance boosts running workloads that are not included on the list of Validated workloads, thanks to nGraph's powerful subgraph pattern matching. Additionally, we have integrated nGraph with PlaidML to provide deep learning performance acceleration on Intel, nVidia, & AMD GPUs. nGraph Compiler aims to accelerate developing AI workloads using any deep learning framework and deploying to a variety of hardware targets. ... -
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CCZero (中国象棋Zero)
Implement AlphaZero/AlphaGo Zero methods on Chinese chess
ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics. -
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DaNNet
Deep Artificial Neural Network framework using Armadillo
DaNNet is a C++ deep neural network library using the Armadillo library as a base. It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network. -
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SLING
A natural language frame semantics parser
...The SLING parser can be trained to produce frame semantic representations of text directly without any explicit intervening linguistic representation. The SLING project is still work in progress. We do not yet have a full system that can extract facts from arbitrary text, but we have built a number of the subsystems needed for such a system. The SLING frame store is our basic framework for building and manipulating frame semantic graph structures. The Wiki flow pipeline can take a raw dump of Wikidata and convert this into one big frame graph. -
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NNVM
Open deep learning compiler stack for cpu, gpu
The vision of the Apache NNVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. Compilation of deep learning models into minimum deployable modules. Infrastructure to automatically generates and optimize models on more backend with better performance.... -
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Apache PredictionIO
Machine learning server for developers and ML engineers
Apache PredictionIO® is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learning task. Quickly build and deploy an engine as a web service on production with customizable templates; respond to dynamic queries in real-time once deployed as a web service; evaluate and tune multiple engine variants systematically; unify data from multiple platforms in batch or in real-time... -
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JCLAL
A Java Class Library for Active Learning
...If you want to refer to JCLAL in a publication, please cite the following JMLR paper. The full citation is: Oscar Reyes, Eduardo Pérez, María del Carmen Rodríguez-Hernández, Habib M. Fardoun, Sebastián Ventura. JCLAL: A Java Framework for Active Learning. Journal of Machine Learning Research, 17(95):1-5, 2016. -
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dlvhex is a prototype solver for HEX-programs which integrate Answer-Set Programs with higher-order reasoning and external computation sources. It comes with a full-fledged plug-in framework for rapid extension development.
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LARA
Lightweight Architecture for boundedly Rational Agents
For the purpose of policy simulation in coupled social-ecological systems (e.g. energy supply), a credible modelling of actors – especially citizens – and their decision processes is needed. This requires a framework capable of handling high numbers of heterogeneous agents (several hundreds of thousands). LARA (Lightweight Architecture for boundedly Rational Agents) meets these requirements and fills the gap between frameworks without built-in psychological foundations and full-fledged cognitive architectures which are both not viable options in this context. ... -
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Full OCR stack for document digitalization analisys and OCR that provide external conexion by API, standard document exchange formats and database.
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This project is a complete cross-platform (Windows, Linux) framework for Evolutionary Computation in pure python. See the project site at http://pyevolve.sourceforge.net or the blog at http://pyevolve.sourceforge.net/wordpress