Search Results for "linux ai" - Page 4
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Showing 216 open source projects for "linux ai"
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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.
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers,... -
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MuseGAN
An AI for Music Generation
MuseGAN is a deep learning research project designed to generate symbolic music using generative adversarial networks. The system focuses specifically on generating multi-track polyphonic music, meaning that it can simultaneously produce multiple instrument parts such as drums, bass, piano, guitar, and strings. Instead of generating raw audio, the model operates on piano-roll representations of music, which encode notes as time-pitch matrices for each instrument track. This representation... -
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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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Burn
Burn is a new comprehensive dynamic Deep Learning Framework
Burn is a new comprehensive dynamic Deep Learning Framework from Tracel AI built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. Burn emphasizes performance, flexibility, and portability for both training and inference. Developed in Rust, it is designed to empower machine learning engineers and researchers across industry and academia. -
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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Robyn
Experimental, AI/ML-powered and open sourced Marketing Mix Modeling
Robyn is an open-source, AI/ML-powered Marketing Mix Modeling (MMM) toolkit developed by Meta Marketing Science under the “facebookexperimental” GitHub umbrella. Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of... -
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ExecuTorch
On-device AI across mobile, embedded and edge for PyTorch
ExecuTorch is an end-to-end solution for enabling on-device inference capabilities across mobile and edge devices including wearables, embedded devices and microcontrollers. It is part of the PyTorch Edge ecosystem and enables efficient deployment of PyTorch models to edge devices. -
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Materials Discovery: GNoME
AI discovers 520000 stable inorganic crystal structures for research
Materials Discovery (GNoME) is a large-scale research initiative by Google DeepMind focused on applying graph neural networks to accelerate the discovery of stable inorganic crystal materials. The project centers on Graph Networks for Materials Exploration (GNoME), a message-passing neural network architecture trained on density functional theory (DFT) data to predict material stability and energy formation. Using GNoME, DeepMind identified 381,000 new stable materials, later expanding the... -
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Humanoid-Gym
Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real
Humanoid-Gym is a reinforcement learning framework designed to train locomotion and control policies for humanoid robots using high-performance simulation environments. The system is built on top of NVIDIA Isaac Gym, which allows large-scale parallel simulation of robotic environments directly on GPU hardware. Its primary goal is to enable efficient training of humanoid robots in simulation while enabling policies to transfer effectively to real-world hardware without additional training.... -
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NVIDIA PhysicsNeMo
Open-source deep-learning framework for building and training
NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building artificial intelligence models that incorporate physical laws and scientific knowledge into machine learning workflows. The framework focuses on the emerging field of physics-informed machine learning, where neural networks are used alongside physical equations to model complex scientific systems. PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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ggml
Tensor library for machine learning
ggml is an open-source tensor library designed for efficient machine learning computation with a focus on running models locally and with minimal dependencies. Written primarily in C and C++, the library provides low-level tensor operations and automatic differentiation that allow developers to implement machine learning algorithms and neural networks efficiently. The project emphasizes portability and performance, enabling machine learning inference across a wide range of hardware... -
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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... -
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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... -
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Deep Learning Interviews book
Hundreds of fully solved job interview questions
The interviews.ai repository hosts the open materials for the book Deep Learning Interviews, a comprehensive collection of technical questions and fully solved problems covering many aspects of artificial intelligence. The project was created to help students, researchers, and engineers prepare for machine learning and deep learning interviews by providing structured explanations of key concepts. The repository organizes problems across topics such as neural networks, optimization,... -
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MLRun
Machine Learning automation and tracking
MLRun is an open MLOps framework for quickly building and managing continuous ML and generative AI applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications, significantly reducing engineering efforts, time to production, and computation resources. MLRun breaks the silos between data, ML, software, and DevOps/MLOps teams, enabling collaboration and fast continuous... -
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The Machine & Deep Learning Compendium
List of references in my private & single document
The Machine & Deep Learning Compendium is an open-source knowledge repository that compiles summaries, references, and learning materials related to machine learning and deep learning. The project functions as a comprehensive compendium that organizes hundreds of topics covering algorithms, frameworks, research areas, and practical machine learning workflows. Originally created as a personal knowledge base, the repository evolved into a public educational resource designed to help learners... -
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Deepnote
Deepnote is a drop-in replacement for Jupyter
Deepnote is an open-source collaborative data science notebook platform designed as a modern alternative to traditional Jupyter notebooks. The project provides an AI-first computational environment where users can write, analyze, and share code, data, and visualizations in a single integrated workspace. Built on top of the Jupyter kernel ecosystem, it maintains compatibility with existing notebook workflows while introducing additional features focused on collaboration and automation. The... -
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SimpleTuner
A general fine-tuning kit geared toward image/video/audio diffusion
SimpleTuner is an open-source toolkit designed to simplify the fine-tuning of modern diffusion models for generating images, video, and audio. The project focuses on providing a clear and understandable training environment for researchers, developers, and artists who want to customize generative AI models without navigating complex machine learning pipelines. It supports fine-tuning workflows for models such as Stable Diffusion variants and other diffusion architectures, enabling users to... -
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Netflix Maestro
Netflix’s Workflow Orchestrator
Maestro is a large-scale workflow orchestration platform originally developed by Netflix to coordinate complex data processing and machine learning workflows across distributed systems. The system acts as a general-purpose workflow orchestrator that manages the execution, scheduling, monitoring, and recovery of large pipelines used for analytics and AI operations. It was designed to support the demanding internal infrastructure of Netflix, where thousands of workflows must process massive... -
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ProjectLearn.io
A curated list of project tutorials for project-based learning
ProjectLearn.io is an open-source repository that aggregates curated tutorials focused on project-based programming education. The project organizes learning resources where users build complete applications from scratch, helping learners acquire practical development experience rather than relying solely on theoretical tutorials. The repository includes projects across multiple domains such as web development, mobile development, machine learning, artificial intelligence, and game... -
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FlexLLMGen
Running large language models on a single GPU
FlexLLMGen is an open-source inference engine designed to run large language models efficiently on limited hardware resources such as a single GPU. The system focuses on high-throughput generation workloads where large batches of text must be processed quickly, such as large-scale data extraction or document analysis tasks. Instead of requiring expensive multi-GPU systems, the framework uses techniques such as memory offloading, compression, and optimized batching to run large models on... -
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The SpeechBrain Toolkit
A PyTorch-based Speech Toolkit
SpeechBrain is an open-source and all-in-one conversational AI toolkit. It is designed to be simple, extremely flexible, and user-friendly. Competitive or state-of-the-art performance is obtained in various domains. SpeechBrain supports state-of-the-art methods for end-to-end speech recognition, including models based on CTC, CTC+attention, transducers, transformers, and neural language models relying on recurrent neural networks and transformers. Speaker recognition is already deployed in a... -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
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Jina
Build cross-modal and multimodal applications on the cloud
Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP,... -
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A Survey of Surveys
A collection of 1000+ survey papers on Natural Language Processing
A Survey of Surveys is a large curated repository that collects and organizes survey papers related to natural language processing, machine learning, and artificial intelligence research. The project aims to provide a centralized index of survey literature that summarizes major developments across different subfields of AI. Rather than focusing on code implementations, the repository functions as an academic resource that helps researchers quickly discover comprehensive survey papers... -
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AI-Aimbot
CS2, Valorant, Fortnite, APEX, every game
AI-Aimbot is a computer vision project that demonstrates how artificial intelligence can be used to automatically identify and target opponents in video games. The system uses an object detection model based on the YOLOv5 architecture to detect human-shaped characters in gameplay screenshots or video frames. Once a target is identified, the program automatically adjusts the player’s aim toward the detected target, effectively automating the aiming process in first-person shooter games. The...
