Search Results for "linux software development" - Page 5
Sort By:
Showing 408 open source projects for "linux software development"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
-
1
PaddlePaddle
PArallel Distributed Deep LEarning: Machine Learning Framework
PaddlePaddle is an open source deep learning industrial platform with advanced technologies and a rich set of features that make innovation and application of deep learning easier. It is the only independent R&D deep learning platform in China, and has been widely adopted in various sectors including manufacturing, agriculture and enterprise service. PaddlePaddle covers core deep learning frameworks, basic model libraries, end-to-end development kits and more, with support for both... -
2
NVIDIA FLARE
NVIDIA Federated Learning Application Runtime Environment
NVIDIA Federated Learning Application Runtime Environment NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows(PyTorch, TensorFlow, Scikit-learn, XGBoost etc.) to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration. NVIDIA FLARE is built on a componentized architecture that allows you to take federated... -
3
mosaicml composer
Supercharge Your Model Training
composer is a deep learning training framework built on PyTorch and designed to make large-scale model training more efficient, scalable, and customizable. At the center of the project is a highly optimized Trainer abstraction that simplifies the management of training loops, parallelization, metrics, logging, and data loading. The framework is intended for modern workloads that may span anything from a single GPU to very large distributed training environments, which makes it suitable for... -
4
Amazing-Python-Scripts
Curated collection of Amazing Python scripts
Amazing-Python-Scripts is a collaborative repository that collects a wide variety of Python scripts designed to demonstrate practical programming techniques and automation tasks. The project includes scripts ranging from beginner-level utilities to more advanced applications involving machine learning, data processing, and system automation. Its goal is to provide developers with useful coding examples that can solve everyday problems, automate repetitive tasks, or serve as learning... -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
-
5
TensorFlow Quantum
Open-source Python framework for hybrid quantum-classical ml learning
TensorFlow Quantum is an open-source software framework designed for building and training hybrid quantum-classical machine learning models within the TensorFlow ecosystem. The framework enables researchers and developers to represent quantum circuits as data and integrate them directly into machine learning workflows. By combining classical deep learning techniques with quantum algorithms, the platform allows experimentation with quantum machine learning methods that may offer advantages... -
6
ChatterBot
Machine learning, conversational dialog engine for creating chat bots
ChatterBot is a Python library that makes it easy to generate automated responses to a user’s input. ChatterBot uses a selection of machine learning algorithms to produce different types of responses. This makes it easy for developers to create chat bots and automate conversations with users. For more details about the ideas and concepts behind ChatterBot see the process flow diagram. The language independent design of ChatterBot allows it to be trained to speak any language. Additionally,... -
7
TNT
A lightweight library for PyTorch training tools and utilities
TNT is a lightweight training framework developed by Meta that simplifies the process of building and managing machine learning training loops using PyTorch. The project focuses on providing a flexible yet structured environment for implementing training pipelines without the complexity of large deep learning frameworks. It introduces modular abstractions that allow developers to organize training logic into reusable components such as trainers, evaluators, and callbacks. This design helps... -
8
MagicMirror²
Modular smart mirror platform with a list of installable modules
MagicMirror² is Open Source, free and maintained by a big group of enthusiasts. Got a nice idea? Send us a pull request and become a part of the big list of contributors. The core of MagicMirror² contains a strong API which allows 3rd party developers to build additional modules. Modules you can use. Modules you can develop. Read our extensive documentation to find out everything you want to know about the MagicMirror² project. The full API description allows you to build your own modules.... -
9
MLX Engine
LM Studio Apple MLX engine
MLX Engine is the Apple MLX-based inference backend used by LM Studio to run large language models efficiently on Apple Silicon hardware. Built on top of the mlx-lm and mlx-vlm ecosystems, the engine provides a unified architecture capable of supporting both text-only and multimodal models. Its design focuses on high-performance on-device inference, leveraging Apple’s MLX stack to accelerate computation on M-series chips. The project introduces modular VisionAddOn components that allow image... -
Earn up to 16% annual interest with Nexo.Generate interest, access liquidity without selling, and execute trades seamlessly. All in one platform. Geographic restrictions, eligibility, and terms apply.
-
10
OpenMLDB
OpenMLDB is an open-source machine learning database
OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference. OpenMLDB is an open-source machine learning database that is committed to solving the data and feature challenges. OpenMLDB has been deployed in hundreds of real-world enterprise applications. It prioritizes the capability of feature engineering using SQL for open-source, which offers a feature platform enabling consistent features for training and... -
11
MLJAR Studio
Python package for AutoML on Tabular Data with Feature Engineering
We are working on new way for visual programming. We developed a desktop application called MLJAR Studio. It is a notebook-based development environment with interactive code recipes and a managed Python environment. All running locally on your machine. We are waiting for your feedback. The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. It is designed to save time for a data scientist. It abstracts the common way to preprocess the data,... -
12
DeepDetect
Deep Learning API and Server in C++14 support for Caffe, PyTorch
The core idea is to remove the error sources and difficulties of Deep Learning applications by providing a safe haven of commoditized practices, all available as a single core. While the Open Source Deep Learning Server is the core element, with REST API, and multi-platform support that allows training & inference everywhere, the Deep Learning Platform allows higher level management for training neural network models and using them as if they were simple code snippets. Ready for applications... -
13
elasticsearch-learning-to-rank
Plugin to integrate Learning to Rank
The Elasticsearch Learning to Rank plugin uses machine learning to improve search relevance ranking. It's powering search at places like Wikimedia Foundation and Snagajob. -
14
CML
Continuous Machine Learning | CI/CD for ML
Continuous Machine Learning (CML) is an open-source CLI tool for implementing continuous integration & delivery (CI/CD) with a focus on MLOps. Use it to automate development workflows, including machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets. CML can help train and evaluate models, and then generate a visual report with results and metrics, automatically on every pull request. -
15
CUTLASS
CUDA Templates for Linear Algebra Subroutines
CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-multiplication (GEMM) and related computations at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS and cuDNN. CUTLASS decomposes these "moving parts" into reusable, modular software components abstracted by C++ template classes. These thread-wide, warp-wide, block-wide, and device-wide... -
16
MediaPipe Solutions
Cross-platform, customizable ML solutions
MediaPipe is an open-source framework developed by Google for building cross-platform machine learning pipelines that process audio, video, and other streaming data in real time. The system provides developers with tools and reusable components that allow them to combine multiple machine learning models with preprocessing and postprocessing logic into efficient perception pipelines. These pipelines can run on a wide variety of platforms including mobile devices, desktop systems, web... -
17
Quantitative Trading System
A comprehensive quantitative trading system with AI-powered analysis
Quantitative Trading System is a comprehensive quantitative trading platform that integrates artificial intelligence, financial data analysis, and automated strategy execution within a unified software system. The project is designed to provide an end-to-end infrastructure for building and operating algorithmic trading strategies in financial markets. It includes tools for collecting and processing market data from multiple sources, performing statistical and machine learning analysis, and... -
18
omegaml
MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle
omega|ml is the innovative Python-native MLOps platform that provides a scalable development and runtime environment for your Data Products. Works from laptop to cloud. -
19
Advanced Solutions Lab
This repos contains notebooks for the Advanced Solutions Lab
This repository contains Jupyter notebooks meant to be run on Vertex AI. This is maintained by Google Cloud’s Advanced Solutions Lab (ASL) team. Vertex AI is the next-generation AI Platform on the Google Cloud Platform. The material covered in this repo will take a software engineer with no exposure to machine learning to an advanced level. -
20
BindsNET
Simulation of spiking neural networks (SNNs) using PyTorch
A Python package used for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch Tensor functionality. BindsNET is a spiking neural network simulation library geared towards the development of biologically inspired algorithms for machine learning. This package is used as part of ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems in the Biologically Inspired Neural & Dynamical Systems (BINDS) lab. -
21
Adversarial Robustness Toolbox
Adversarial Robustness Toolbox (ART) - Python Library for ML security
Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to evaluate, defend, certify and verify Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, sci-kit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio,... -
22
shimmy
Python-free Rust inference server
The shimmy project is a lightweight local inference server designed to run large language models with minimal overhead. Written primarily in Rust, the tool provides a small standalone binary that exposes an API compatible with the OpenAI interface, allowing existing applications to interact with local models without significant code changes. This compatibility enables developers to replace remote AI services with locally hosted models while keeping their existing software architecture... -
23
HivisionIDPhoto
HivisionIDPhotos: a lightweight and efficient AI ID photos tools
HivisionIDPhotos is an open-source AI project designed to automatically generate professional ID photographs from ordinary portrait images. The system uses computer vision and machine learning models to detect faces, segment the subject from the background, and produce standardized identification photos suitable for official documents. It is designed as a lightweight tool that can perform inference offline and run efficiently on CPUs without requiring powerful GPUs. The software analyzes... -
24
GROBID
A machine learning software for extracting information
GROBID is a machine learning library for extracting, parsing, and re-structuring raw documents such as PDF into structured XML/TEI encoded documents with a particular focus on technical and scientific publications. First developments started in 2008 as a hobby. In 2011 the tool has been made available in open source. Work on GROBID has been steady as a side project since the beginning and is expected to continue as such. Header extraction and parsing from article in PDF format. The... -
25
AlphaTree
DNN && GAN && NLP && BIG DATA
AlphaTree is an educational repository that provides a visual roadmap of deep learning models and related artificial intelligence technologies. The project focuses on explaining the historical development and relationships between major neural network architectures used in modern machine learning. It presents diagrams and documentation describing the evolution of models such as LeNet, AlexNet, VGG, ResNet, DenseNet, and Inception networks. The repository organizes these architectures into a...
