Search Results for "virtual windows machine" - Page 6

Showing 1313 open source projects for "virtual windows machine"

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  • 1
    MNE-Python

    MNE-Python

    Magnetoencephalography (MEG) and Electroencephalography EEG in Python

    Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data. MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more.
    Downloads: 2 This Week
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  • 2
    StatsForecast

    StatsForecast

    Fast forecasting with statistical and econometric models

    StatsForecast is a Python library for time-series forecasting that delivers a suite of classical statistical and econometric forecasting models optimized for high performance and scalability. It is designed not just for academic experiments but for production-level time-series forecasting, meaning it handles forecasting for many series at once, efficiently, reliably, and with minimal overhead. The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery...
    Downloads: 9 This Week
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  • 3
    MLRun

    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...
    Downloads: 4 This Week
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  • 4
    PyQuil

    PyQuil

    A Python library for quantum programming using Quil

    PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. To...
    Downloads: 4 This Week
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  • 5
    Video-subtitle-extractor

    Video-subtitle-extractor

    A GUI tool for extracting hard-coded subtitle (hardsub) from videos

    Video hard subtitle extraction, generate srt file. There is no need to apply for a third-party API, and text recognition can be implemented locally. A deep learning-based video subtitle extraction framework, including subtitle region detection and subtitle content extraction. A GUI tool for extracting hard-coded subtitles (hardsub) from videos and generating srt files. Use local OCR recognition, no need to set up and call any API, and do not need to access online OCR services such as Baidu...
    Downloads: 70 This Week
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  • 6
    E2B Desktop Sandbox

    E2B Desktop Sandbox

    E2B Desktop Sandbox for LLMs. E2B Sandbox

    E2B Desktop is an open-source sandboxed virtual desktop environment designed to enable secure “computer use” by large language models and automated agents. The platform provides isolated virtual machines where applications can be executed safely without affecting the host system. Each sandbox runs independently and can be configured with custom dependencies or tools required by an AI agent or automation workflow. The system allows developers to programmatically create and control these...
    Downloads: 0 This Week
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  • 7
    FlashAttention

    FlashAttention

    Fast and memory-efficient exact attention

    FlashAttention is a high-performance deep learning optimization library that reimplements the attention mechanism used in transformer models to be significantly faster and more memory-efficient than standard implementations. It achieves this by using IO-aware algorithms that minimize memory reads and writes, reducing the quadratic memory overhead typically associated with attention operations. The project provides implementations of FlashAttention, FlashAttention-2, and newer iterations...
    Downloads: 27 This Week
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  • 8
    EasyOCR

    EasyOCR

    Ready-to-use OCR with 80+ supported languages

    Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc. EasyOCR is a python module for extracting text from image. It is a general OCR that can read both natural scene text and dense text in document. We are currently supporting 80+ languages and expanding. Second-generation models: multiple times smaller size, multiple times faster inference, additional characters and comparable accuracy to the first...
    Downloads: 38 This Week
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  • 9
    Determined

    Determined

    Determined, deep learning training platform

    The fastest and easiest way to build deep learning models. Distributed training without changing your model code. Determined takes care of provisioning machines, networking, data loading, and fault tolerance. Build more accurate models faster with scalable hyperparameter search, seamlessly orchestrated by Determined. Use state-of-the-art algorithms and explore results with our hyperparameter search visualizations. Interpret your experiment results using the Determined UI and TensorBoard, and...
    Downloads: 26 This Week
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  • 10
    lightning AI

    lightning AI

    The most intuitive, flexible, way for researchers to build models

    Build in days not months with the most intuitive, flexible framework for building models and Lightning Apps (ie: ML workflow templates) which "glue" together your favorite ML lifecycle tools. Build models and build/publish end-to-end ML workflows that "glue" your favorite tools together. Models are “easy”, the “glue” work is hard. Lightning Apps are community-built templates that stitch together your favorite ML lifecycle tools into cohesive ML workflows that can run on your laptop or any...
    Downloads: 10 This Week
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  • 11
    LLM CLI

    LLM CLI

    Access large language models from the command-line

    A CLI utility and Python library for interacting with Large Language Models, both via remote APIs and models that can be installed and run on your own machine.
    Downloads: 4 This Week
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  • 12
    Petastorm

    Petastorm

    Petastorm library enables single machine or distributed training

    Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular...
    Downloads: 0 This Week
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  • 13
    AI-Tutorials/Implementations Notebooks

    AI-Tutorials/Implementations Notebooks

    Codes/Notebooks for AI Projects

    AI-Tutorials/Implementations Notebooks repository is a comprehensive collection of artificial intelligence tutorials and implementation examples intended for developers, students, and researchers who want to learn by building practical AI projects. The repository contains numerous Jupyter notebooks and code samples that demonstrate modern techniques in machine learning, deep learning, data science, and large language model workflows. It includes implementations for a wide range of AI topics...
    Downloads: 0 This Week
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  • 14
    Featuretools

    Featuretools

    An open source python library for automated feature engineering

    An open source Python framework for automated feature engineering. Featuretools automatically creates features from temporal and relational datasets. Featuretools uses DFS for automated feature engineering. You can combine your raw data with what you know about your data to build meaningful features for machine learning and predictive modeling. Featuretools provides APIs to ensure only valid data is used for calculations, keeping your feature vectors safe from common label leakage problems....
    Downloads: 0 This Week
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  • 15
    TensorFlow Datasets

    TensorFlow Datasets

    TFDS is a collection of datasets ready to use with TensorFlow,

    TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax. All datasets are exposed as tf.data. Datasets , enabling easy-to-use and high-performance input pipelines. To get started see the guide and our list of datasets.
    Downloads: 5 This Week
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  • 16
    ContextForge MCP Gateway

    ContextForge MCP Gateway

    A Model Context Protocol (MCP) Gateway & Registry

    MCP Context Forge is a feature-rich gateway and registry that federates Model Context Protocol (MCP) servers and traditional REST services behind a single, governed endpoint. It exposes an MCP-compliant interface to clients while handling discovery, authentication, rate limiting, retries, and observability on the server side. The gateway scales horizontally, supports multi-cluster deployments on Kubernetes, and uses Redis for federation and caching across instances. Operators can define...
    Downloads: 13 This Week
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  • 17
    HY-World 1.5

    HY-World 1.5

    A Systematic Framework for Interactive World Modeling

    HY-WorldPlay is a Hunyuan AI project focusing on immersive multimodal content generation and interaction within virtual worlds or simulated environments. It aims to empower AI agents with the capability to both understand and generate multimedia content — including text, audio, image, and potentially 3D or game-world elements — enabling lifelike dialogue, environmental interpretations, and responsive world behavior. The platform targets use cases in digital entertainment, game worlds,...
    Downloads: 18 This Week
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  • 18
    TorchCode

    TorchCode

    Practice implementing softmax, attention, GPT-2 and more

    TorchCode is an interactive learning and practice platform designed to help developers master PyTorch by implementing core machine learning operations and architectures from scratch. It is structured similarly to competitive programming platforms like LeetCode but focuses specifically on tensor operations and deep learning concepts. The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms,...
    Downloads: 2 This Week
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  • 19
    Cube Studio

    Cube Studio

    Cube Studio open source cloud native one-stop machine learning

    Cube Studio is an open-source, cloud-native end-to-end machine learning and AI platform designed to support the full lifecycle of AI development — from data preparation and interactive notebook coding to distributed training, model tuning, and deployment in production-ready environments. It provides a unified interface where teams can manage data sources, track datasets, and build pipelines using drag-and-drop workflow orchestration, making it accessible for both engineers and data...
    Downloads: 4 This Week
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  • 20
    Bytewax

    Bytewax

    Python Stream Processing

    Bytewax is a Python framework that simplifies event and stream processing. Because Bytewax couples the stream and event processing capabilities of Flink, Spark, and Kafka Streams with the friendly and familiar interface of Python, you can re-use the Python libraries you already know and love. Connect data sources, run stateful transformations, and write to various downstream systems with built-in connectors or existing Python libraries. Bytewax is a Python framework and Rust distributed...
    Downloads: 4 This Week
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  • 21
    UMAP

    UMAP

    Uniform Manifold Approximation and Projection

    Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualization similarly to t-SNE, but also for general non-linear dimension reduction. It is possible to model the manifold with a fuzzy topological structure. The embedding is found by searching for a low-dimensional projection of the data that has the closest possible equivalent fuzzy topological structure. First of all UMAP is fast. It can handle large datasets and high dimensional...
    Downloads: 4 This Week
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  • 22
    OpenRLHF

    OpenRLHF

    An Easy-to-use, Scalable and High-performance RLHF Framework

    OpenRLHF is an easy-to-use, scalable, and high-performance framework for Reinforcement Learning with Human Feedback (RLHF). It supports various training techniques and model architectures.
    Downloads: 7 This Week
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  • 23
    Hermes Agent

    Hermes Agent

    The agent that grows with you

    Hermes Agent is a fully open-source autonomous AI agent designed to run persistently on your own machine or server, becoming more capable the longer it operates by learning from experience and building reusable procedural skills. Rather than functioning as a stateless chatbot, it maintains long-term memory across sessions and can generate searchable “Skill Documents” that capture how it solved complex tasks so it doesn’t start from scratch each time. The agent interfaces with messaging...
    Downloads: 168 This Week
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  • 24
    Ray

    Ray

    A unified framework for scalable computing

    Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best...
    Downloads: 3 This Week
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  • 25
    SDGym

    SDGym

    Benchmarking synthetic data generation methods

    ...Select any of the publicly available datasets from the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. Install SDGym using pip or conda. We recommend using a virtual environment to avoid conflicts with other software on your device.
    Downloads: 7 This Week
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