Showing 498 open source projects for "google-visualization-python"

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  • 1
    Jraph

    Jraph

    A Graph Neural Network Library in Jax

    Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time compilation. ...
    Downloads: 0 This Week
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  • 2
    Facexlib

    Facexlib

    FaceXlib aims at providing ready-to-use face-related functions

    facexlib is a PyTorch-based library providing ready-to-use face-related functions, including detection, alignment, recognition, and more. It integrates state-of-the-art open-source methods for various face processing tasks.​
    Downloads: 0 This Week
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  • 3
    Hacker Scripts

    Hacker Scripts

    Based on a true story

    ...The README explains the origin story and highlights several canonical scripts and provides usage notes such as required environment variables and cron examples for scheduling. Contributors have provided implementations and ports in many languages and folders (shell, Ruby, Python, Node, Perl, PowerShell, Go, Java, etc.), and the project explicitly welcomes pull requests that add additional language implementations.
    Downloads: 41 This Week
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  • 4
    PyTorch Transfer-Learning-Library

    PyTorch Transfer-Learning-Library

    Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.

    TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please...
    Downloads: 1 This Week
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  • 5
    Fairseq

    Fairseq

    Facebook AI Research Sequence-to-Sequence Toolkit written in Python

    Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. ...
    Downloads: 0 This Week
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  • 6
    osm4scala

    osm4scala

    Reading OpenStreetMap Pbf files.

    Scala and polyglot Spark library (Scala, PySpark, SparkSQL, ... ) focused on reading OpenStreetMap Pbf files.
    Downloads: 0 This Week
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  • 7
    Whisper Library

    Whisper Library

    Whisper is a file-based time-series database format for Graphite

    Whisper is one of three components within the Graphite project. Whisper is a fixed-size database, similar in design and purpose to RRD (round-robin-database). It provides fast, reliable storage of numeric data over time. Whisper allows for higher resolution (seconds per point) of recent data to degrade into lower resolutions for long-term retention of historical data. Copies data from src in dst, if missing. Unlike whisper-merge, don't overwrite data that's already present in the target...
    Downloads: 0 This Week
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  • 8
    Binarytree

    Binarytree

    Python library for studying Binary Trees

    Binarytree is Python library that lets you generate, visualize, inspect and manipulate binary trees. Skip the tedious work of setting up test data, and dive straight into practicing algorithms. Heaps and BSTs (binary search trees) are also supported. Binarytree supports another representation which is more compact but without the indexing properties.
    Downloads: 0 This Week
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  • 9
    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: 0 This Week
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  • 10
    SageMaker Scikit-Learn Extension

    SageMaker Scikit-Learn Extension

    A library of additional estimators and SageMaker tools based on scikit

    ...For unit tests, tox will use pytest to run the unit tests in a Python 3.7 interpreter. tox will also run flake8 and pylint for style checks.
    Downloads: 0 This Week
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  • 11
    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 protocols and transports. ...
    Downloads: 2 This Week
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  • 12
    Interpret-Text

    Interpret-Text

    State-of-the-art explainers for text-based machine learning models

    A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard. Interpret-Text builds on Interpret, an open source python package for training interpretable models and helping to explain blackbox machine learning systems. We have added extensions to support text models. Interpret-Text incorporates community-developed interpretability techniques for NLP models and a visualization dashboard to view the results. Users can run their experiments across multiple state-of-the-art explainers and easily perform comparative analysis on them. ...
    Downloads: 0 This Week
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  • 13
    SVoice (Speech Voice Separation)

    SVoice (Speech Voice Separation)

    We provide a PyTorch implementation of the paper Voice Separation

    SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple...
    Downloads: 1 This Week
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  • 14
    GDAL wheels for linux

    GDAL wheels for linux

    GDAL wheels for python and C/C++ projects (Linux only)

    To use precompiled wheels: 1) go to releases (Files) and download tarball needed; 2) install it with command: python3 -m pip install /path/to/wheel.whl Or simply use URL in pip: python3 -m pip install https://sourceforge.net/projects/gdal-wheels-for-linux/files/GDAL-3.1.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl/download URL may be found under "View details" button (i) To use GDAL in C/C++ project you need to link gdal lib AND all libs located at dir GDAL.libs (usually this folder resides inside python site-packages) To compile your own wheels see information given at forefather project: https://github.com/youngpm/gdalmanylinux Usually this is done via command `make wheels` GDAL wheels for Windows are provided by Christoph Gohlke at https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal Built with PROJ (proj.db is included), GEOS, EXPAT. ...
    Downloads: 33 This Week
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  • 15
    Awesome Fraud Detection Research Papers

    Awesome Fraud Detection Research Papers

    A curated list of data mining papers about fraud detection

    A curated list of data mining papers about fraud detection from several conferences.
    Downloads: 0 This Week
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  • 16
    Nimporter

    Nimporter

    Compile Nim Extensions for Python On Import

    Nimporter allows the seamless import of Nim code into Python projects, enabling the use of Nim's performance and syntax within Python applications.
    Downloads: 0 This Week
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  • 17
    TensorNetwork

    TensorNetwork

    A library for easy and efficient manipulation of tensor networks

    ...Because it supports backends such as NumPy, TensorFlow, PyTorch, and JAX, the same model can run on CPUs, GPUs, or TPUs with minimal code changes. Tutorials and visualization helpers make it easier to understand how network topology affects expressive power and computational cost.
    Downloads: 0 This Week
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  • 18
    TensorFlow Examples

    TensorFlow Examples

    TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

    TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or...
    Downloads: 2 This Week
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  • 19
    Spleeter

    Spleeter

    Deezer source separation library including pretrained models

    ...We designed Spleeter so you can use it straight from command line as well as directly in your own development pipeline as a Python library. It can be installed with Conda, with pip or be used with Docker.
    Downloads: 93 This Week
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  • 20
    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.
    Downloads: 0 This Week
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  • 21
    Pandas TA

    Pandas TA

    Python 3 Pandas Extension with 130+ Indicators

    Technical Analysis Indicators - Pandas TA is an easy-to-use Python 3 Pandas Extension with 130+ Indicators. Pandas Technical Analysis (Pandas TA) is an easy-to-use library that leverages the Pandas package with more than 130 Indicators and Utility functions and more than 60 TA Lib Candlestick Patterns. Many commonly used indicators are included, such as: Candle Pattern(cdl_pattern), Simple Moving Average (sma) Moving Average Convergence Divergence (macd), Hull Exponential Moving Average (hma), Bollinger Bands (bbands), On-Balance Volume (obv), Aroon & Aroon Oscillator (aroon), Squeeze (squeeze) and many more.
    Downloads: 114 This Week
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  • 22
    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...
    Downloads: 0 This Week
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  • 23
    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.
    Downloads: 0 This Week
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  • 24
    ReinventCommunity

    ReinventCommunity

    Jupyter Notebook tutorials for REINVENT 3.2

    This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2.
    Downloads: 0 This Week
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  • 25
    pbxproj

    pbxproj

    A python module to manipulate XCode projects

    ...The file is usually called project.pbxproj and can be found inside the .xcodeproj bundle. Because some tasks cannot be done by clicking on a UI or opening Xcode to do it for you, this Python module lets you automate the modification process. The typical tasks with an Xcode project are adding files to the project and setting some standard compilation flags.
    Downloads: 0 This Week
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