Showing 94 open source projects for "linux xp like"

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  • 1
    fvcore

    fvcore

    Collection of common code shared among different research projects

    fvcore is a lightweight utility library that factors out common performance-minded components used across Facebook/Meta computer-vision codebases. It provides numerics and loss layers (e.g., focal loss, smooth-L1, IoU/GIoU) implemented for speed and clarity, along with initialization helpers and normalization layers for building PyTorch models. Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. A...
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  • 2
    Flama

    Flama

    Fire up your models with the flame

    Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. Besides, it comprises an ideal solution...
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  • 3
    Python Outlier Detection

    Python Outlier Detection

    A Python toolbox for scalable outlier detection

    PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural...
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  • 4
    sqlite-utils

    sqlite-utils

    Python CLI utility and library for manipulating SQLite databases

    sqlite-utils is both a Python library and a command-line tool for creating, inspecting, and transforming SQLite databases with minimal boilerplate. It focuses on making common tasks like importing CSV/JSON, exploring tables, and running ad-hoc queries feel ergonomic and scriptable. As a CLI, it lets you build databases from structured data in one line, run queries against local files or in-memory databases, output results as JSON, CSV, or pretty tables, and configure full-text search. As a...
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  • 5
    aws-devops-zero-to-hero

    aws-devops-zero-to-hero

    AWS zero to hero repo for devops engineers to learn AWS in 30 Days

    aws-devops-zero-to-hero is a 30-day AWS learning roadmap aimed squarely at DevOps engineers who want both conceptual understanding and hands-on projects. The README is structured as a day-by-day syllabus, starting with “Day 1: Introduction to AWS” and moving through IAM, EC2, VPC networking, security, DNS (Route 53), storage (S3), and many other core services. Each day mixes explanation with at least one concrete project or lab, such as deploying applications on EC2, designing secure VPCs,...
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  • 6
    Graphtage

    Graphtage

    A semantic diff utility and library for tree-like files such as JSON

    Graphtage is a command-line utility and underlying library for semantically comparing and merging tree-like structures, such as JSON, XML, HTML, YAML, plist, and CSS files. Its name is a portmanteau of “graph” and “graftage”, the latter being the horticultural practice of joining two trees together such that they grow as one. Graphtage performs an analysis on an intermediate representation of the trees that is divorced from the filetypes of the input files. This means, for example, that you...
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  • 7
    Transformers4Rec

    Transformers4Rec

    Transformers4Rec is a flexible and efficient library

    Transformers4Rec is an advanced recommendation system library that leverages Transformer models for sequential and session-based recommendations. The library works as a bridge between natural language processing (NLP) and recommender systems (RecSys) by integrating with one of the most popular NLP frameworks, Hugging Face Transformers (HF). Transformers4Rec makes state-of-the-art transformer architectures available for RecSys researchers and industry practitioners. Traditional recommendation...
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  • 8
    lixa

    lixa

    LIXA, LIbre XA, is a free and open source XA transaction manager

    LIXA (LIbre XA) is an open source and free Transaction Manager implementing the distributed transaction processing "XA specification" and "TX (transaction demarcation) specification" according to the X/Open CAE Specification. LIXA implements even XTA: XA Transaction API, an innovative API that implements XA transactional context passing among different applications. LIXA is a Transaction Manager but it's not a Transaction Monitor: this is the distinguishing feature of the project. LIXA...
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  • 9
    Neural Tangents

    Neural Tangents

    Fast and Easy Infinite Neural Networks in Python

    Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,...
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  • 10
    databooks

    databooks

    A CLI tool to reduce the friction between data scientists

    databooks is a package to ease the collaboration between data scientists using Jupyter notebooks, by reducing the number of git conflicts between different notebooks and resolution of git conflicts when encountered. Simply specify the paths for notebook files to remove metadata. By doing so, we can already avoid many of the conflicts. Specify the paths for notebook files with conflicts to be fixed. Then, databooks finds the source notebooks that caused the conflicts and compares them (so no...
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  • 11
    Neural Network Intelligence

    Neural Network Intelligence

    AutoML toolkit for automate machine learning lifecycle

    Neural Network Intelligence is an open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning and model compression. The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments'...
    Downloads: 2 This Week
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  • 12
    DeepMind Research

    DeepMind Research

    Implementations and code to accompany DeepMind publications

    This repository collects reference implementations and illustrative code accompanying a wide range of DeepMind publications, making it easier for the research community to reproduce results, inspect algorithms, and build on prior work. The top level organizes many paper-specific directories across domains such as deep reinforcement learning, self-supervised vision, generative modeling, scientific ML, and program synthesis—for example BYOL, Perceiver/Perceiver IO, Enformer for genomics,...
    Downloads: 1 This Week
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  • 13
    Robin-Stocks API Library

    Robin-Stocks API Library

    This is a library to use with Robinhood Financial App

    This is a library to use with Robinhood Financial App. It currently supports trading crypto-currencies, options, and stocks. In addition, it can be used to get real-time ticker information, assess the performance of your portfolio, and can also get tax documents, total dividends paid, and more. The code is simple to use, easy to understand, and easy to modify. With this library, you can view information on stocks, options, and cryptocurrencies in real-time, create your own robo-investor or...
    Downloads: 1 This Week
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  • 14
    CARTOframes

    CARTOframes

    CARTO Python package for data scientists

    A Python package for integrating CARTO maps, analysis, and data services into data science workflows. Python data analysis workflows often rely on the de facto standards pandas and Jupyter notebooks. Integrating CARTO into this workflow saves data scientists time and energy by not having to export datasets as files or retain multiple copies of the data. Instead, CARTOframes give the ability to communicate reproducible analysis while providing the ability to gain from CARTO's services like...
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  • 15
    Buildozer

    Buildozer

    Generic Python packager for Android and iOS

    ...Buildozer will use that spec to create a package for Android, iOS, Windows, OSX and/or Linux.
    Downloads: 40 This Week
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  • 16
    NeuMan

    NeuMan

    Neural Human Radiance Field from a Single Video (ECCV 2022)

    NeuMan is a reference implementation that reconstructs both an animatable human and its background scene from a single monocular video using neural radiance fields. It supports novel view and novel pose synthesis, enabling compositional results like transferring reconstructed humans into new scenes. The pipeline separates human/body and environment, learning consistent geometry and appearance to support animation. Demos showcase sequences such as dance and handshake, and the code provides...
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  • 17
    Name-That-Hash

    Name-That-Hash

    Identify MD5, SHA256 and 300+ other hashes

    Name-That-Hash is a modern hash identification system that tells you what type of hash you are looking at, supporting MD5, SHA-256, and more than 300 other hash types. It is designed as a successor and improvement to older tools like HashID and Hash-Identifier, focusing on up-to-date hash databases and better usability. One of its core ideas is popularity-aware ranking: when you feed in a hash, it prioritizes likely real-world types such as NTLM over obscure ones like Skype hashes, instead...
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  • 18
    AugLy

    AugLy

    A data augmentations library for audio, image, text, and video

    AugLy is a data augmentations library that currently supports four modalities (audio, image, text & video) and over 100 augmentations. Each modality’s augmentations are contained within its own sub-library. These sub-libraries include both function-based and class-based transforms, composition operators, and have the option to provide metadata about the transform applied, including its intensity. AugLy is a great library to utilize for augmenting your data in model training, or to evaluate...
    Downloads: 1 This Week
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  • 19
    Spyne

    Spyne

    A transport agnostic sync/async RPC library

    Spyne is a Python RPC toolkit that makes it easy to expose online services that have a well-defined API using multiple protocols and transports. It integrates with popular Python web frameworks as well as libraries like SQLAlchemy to keep your code as DRY as possible. Spyne aims to save the protocol implementers the hassle of implementing their own remote procedure call api and the application programmers the hassle of jumping through hoops just to expose their services using multiple...
    Downloads: 0 This Week
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  • 20
    PyTorchVideo

    PyTorchVideo

    A deep learning library for video understanding research

    PyTorchVideo is a deep learning library for video understanding, providing modular components and pretrained models for tasks like action recognition, video classification, detection, and self-supervised learning. It is tightly integrated with PyTorch and PyTorch Lightning, offering flexible APIs for building and training spatiotemporal networks. The library includes efficient implementations of state-of-the-art architectures such as SlowFast, X3D, and MViT, optimized for both research...
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  • 21
    TRFL

    TRFL

    TensorFlow Reinforcement Learning

    TRFL, developed by Google DeepMind, is a TensorFlow-based library that provides a collection of essential building blocks for reinforcement learning (RL) algorithms. Pronounced “truffle,” it simplifies the implementation of RL agents by offering reusable components such as loss functions, value estimation tools, and temporal difference (TD) learning operators. The library is designed to integrate seamlessly with TensorFlow, allowing users to define differentiable RL objectives and train...
    Downloads: 0 This Week
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  • 22
    Differentiable Neural Computer

    Differentiable Neural Computer

    A TensorFlow implementation of the Differentiable Neural Computer

    The Differentiable Neural Computer (DNC), developed by Google DeepMind, is a neural network architecture augmented with dynamic external memory, enabling it to learn algorithms and solve complex reasoning tasks. Published in Nature in 2016 under the paper “Hybrid computing using a neural network with dynamic external memory,” the DNC combines the pattern recognition power of neural networks with a memory module that can be written to and read from in a differentiable way. This allows the...
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  • 23
    earthengine-py-notebooks

    earthengine-py-notebooks

    A collection of 360+ Jupyter Python notebook examples

    earthengine-py-notebooks is a comprehensive collection of hundreds of Jupyter Python notebooks that serve as examples and tutorials for using the Google Earth Engine Python API. These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and...
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  • 24
    Zipline

    Zipline

    Zipline, a Pythonic algorithmic trading library

    Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python...
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  • 25
    SentEval

    SentEval

    A python tool for evaluating the quality of sentence embeddings

    SentEval is a standardized toolkit for evaluating sentence embeddings across a wide spectrum of downstream tasks and probing tests. It defines a simple interface—provide an encoder function from sentences to vectors—and then runs consistent training/evaluation loops for tasks like sentiment, entailment, paraphrase, and semantic textual similarity. The suite also contains linguistic probing tasks that illuminate what properties embeddings capture, such as tense, word order, or syntactic...
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