Showing 1024 open source projects for "linux is"

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  • 1

    SwaNN

    PSO for neural networks

    SwaNN is a basic framework for neural networks based on particle swarm optimization (using the Python package PySwarms (https://pyswarms.readthedocs.io/en/latest/). The zip file contains the main programs in SwaNN.py and around 30 examples : - classification - regression - time series forecasting I need some help for class building (I am not an expert in Python nor in OOP), if somebody is interested in it... In Google Colab :...
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  • 2
    Java Neural Network Framework Neuroph
    Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
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    Downloads: 70 This Week
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  • 3
    TensorNets

    TensorNets

    High level network definitions with pre-trained weights in TensorFlow

    High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 >= TF >= 1.4.0). Applicability. Many people already have their own ML workflows and want to put a new model on their workflows. TensorNets can be easily plugged together because it is designed as simple functional interfaces without custom classes. Manageability. Models are written in tf.contrib.layers, which is lightweight like PyTorch and Keras, and allows for ease of accessibility to every weight and...
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  • 4
    NLP Best Practices

    NLP Best Practices

    Natural Language Processing Best Practices & Examples

    In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive business adoption of artificial intelligence (AI) solutions. In the last few years, researchers have been applying newer deep learning methods to NLP. Data scientists started moving from traditional methods to state-of-the-art (SOTA) deep neural network (DNN) algorithms which use language models pretrained on large text corpora. This repository contains examples and...
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  • 5
    TensorFlow Object Counting API

    TensorFlow Object Counting API

    The TensorFlow Object Counting API is an open source framework

    The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems. Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the...
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  • 6
    NLP-progress

    NLP-progress

    Repository to track the progress in Natural Language Processing (NLP)

    Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks. This document aims to track the progress in Natural Language Processing (NLP) and give an overview of the state-of-the-art (SOTA) across the most common NLP tasks and their corresponding datasets. It aims to cover both traditional and core NLP tasks such as dependency parsing and part-of-speech tagging as well as more recent ones such...
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  • 7
    awesome-TS-anomaly-detection

    awesome-TS-anomaly-detection

    List of tools & datasets for anomaly detection on time-series data

    All lists are in alphabetical order. In the lists, maintained projects are prioritized vs not mantained. A repository is considered "not maintained" if the latest commit is > 1 year old, or explicitly mentioned by the authors.
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  • 8
    A.I. Stock Trends With WEKA & TA-Lib

    A.I. Stock Trends With WEKA & TA-Lib

    A Repository Of The Java Programs Presented in the Videos.

    This is the open/public source code repository for the Java programs shown in the YouTube videos - A.I. Stock Trends With WEKA, TA-Lib and more https://www.youtube.com/channel/UCPxmgFZDS7F06UBBxH5b4mg
    Downloads: 0 This Week
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  • 9
    BytePS

    BytePS

    A high performance and generic framework for distributed DNN training

    BytePS is a high-performance and generally distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on either TCP or RDMA networks. BytePS outperforms existing open-sourced distributed training frameworks by a large margin. For example, on BERT-large training, BytePS can achieve ~90% scaling efficiency with 256 GPUs (see below), which is much higher than Horovod+NCCL. In certain scenarios, BytePS can double the training speed compared with Horovod+NCCL....
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  • 10
    ChainerRL

    ChainerRL

    ChainerRL is a deep reinforcement learning library

    ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments...
    Downloads: 0 This Week
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  • 11
    imgaug

    imgaug

    Image augmentation for machine learning experiments

    imgaug is a library for image augmentation in machine learning experiments. It supports a wide range of augmentation techniques, allows to easily combine these and to execute them in random order or on multiple CPU cores, has a simple yet powerful stochastic interface and can not only augment images but also key points/landmarks, bounding boxes, heatmaps and segmentation maps. Affine transformations, perspective transformations, contrast changes, gaussian noise, dropout of regions,...
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  • 12
    CrypTen

    CrypTen

    A framework for Privacy Preserving Machine Learning

    CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic...
    Downloads: 0 This Week
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  • 13
    textgenrnn

    textgenrnn

    Easily train your own text-generating neural network

    With textgenrnn you can easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code. A modern neural network architecture that utilizes new techniques as attention-weighting and skip-embedding to accelerate training and improve model quality. Train on and generate text at either the character-level or word-level. Configure RNN size, the number of RNN layers, and whether to use bidirectional RNNs. Train on any generic input text...
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  • 14
    Spinning Up in Deep RL

    Spinning Up in Deep RL

    Educational resource to help anyone learn deep reinforcement learning

    Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the...
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  • 15
    Diff Zoo

    Diff Zoo

    Differentiation for Hackers

    Diff-zoo is a learning-focused handbook designed to demystify algorithmic differentiation (AD), the core technique powering modern machine learning frameworks. The project introduces AD from a foundational calculus perspective and gradually builds towards toy implementations that resemble systems like PyTorch and TensorFlow. It clarifies the differences and connections between forward mode, reverse mode, symbolic, numeric, tracing, and source transformation approaches to differentiation....
    Downloads: 2 This Week
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  • 16
    MMSkeleton

    MMSkeleton

    A OpenMMLAB toolbox for human pose estimation, skeleton-based action

    MMSkeleton is an open-source toolbox for skeleton-based human understanding. It is a part of the open-mmlab project in the charge of Multimedia Laboratory, CUHK. MMSkeleton is developed on our research project ST-GCN. MMSkeleton provides a flexible framework for organizing codes and projects systematically, with the ability to extend to various tasks and scale up to complex deep models. MMSkeleton addresses to multiple tasks in human understanding. Build a custom skeleton-based dataset....
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  • 17
    Image Super-Resolution (ISR)

    Image Super-Resolution (ISR)

    Super-scale your images and run experiments with Residual Dense

    The goal of this project is to upscale and improve the quality of low-resolution images. This project contains Keras implementations of different Residual Dense Networks for Single Image Super-Resolution (ISR) as well as scripts to train these networks using content and adversarial loss components. Docker scripts and Google Colab notebooks are available to carry training and prediction. Also, we provide scripts to facilitate training on the cloud with AWS and Nvidia-docker with only a few...
    Downloads: 1 This Week
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  • 18
    Manifold ML

    Manifold ML

    A model-agnostic visual debugging tool for machine learning

    Manifold is a model-agnostic visual debugging tool for machine learning. Understanding ML model performance and behavior is a non-trivial process, given the intrisic opacity of ML algorithms. Performance summary statistics such as AUC, RMSE, and others are not instructive enough to identify what went wrong with a model or how to improve it. As a visual analytics tool, Manifold allows ML practitioners to look beyond overall summary metrics to detect which subset of data a model is...
    Downloads: 0 This Week
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  • 19
    Python Machine Learning

    Python Machine Learning

    The "Python Machine Learning (2nd edition)" book code repository

    This repository accompanies the well-known textbook “Python Machine Learning, 2nd Edition” by Sebastian Raschka and Vahid Mirjalili, serving as a complete codebase of examples, notebooks, scripts and supporting materials for the book. It covers a wide range of topics including supervised learning, unsupervised learning, dimensionality reduction, model evaluation, deep learning with TensorFlow, and embedding models into web apps. Each chapter has Jupyter notebooks and Python scripts that...
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  • 20
    Speech Recognition in English & Polish

    Speech Recognition in English & Polish

    Speech recognition software for English & Polish languages

    Software for speech recognition in English & Polish languages. Basic versions of SkryBot: 1. SkryBot Home Speech (English Language) - https://sourceforge.net/projects/skrybotdomowy/files/ReleasesEnglish/InstalatorSkryBotHomeSpeechDemo-2.6.9.18117.exe/download 2. SkryBot DoMowy (Polish Language) - https://sourceforge.net/projects/skrybotdomowy/files/ReleasesPolish/InstalatorSkryBotDoMowyDemo-2.4.9.18117.exe/download More...
    Downloads: 1 This Week
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  • 21

    rpackage conjurer

    Synthetic data generation using R

    Builds synthetic data applicable across multiple domains. This package also provides flexibility to control data distribution to make it relevant to many industry examples.
    Downloads: 0 This Week
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  • 22
    Phenalysis

    Phenalysis

    Analyze agronomic plant research plots in aerial orthomosaic images.

    A graphical user interface to import, analyze and export plots from orthomosaic images of agronomic trials. Please cite the following reference in your work if you use Phenalysis: Khan Z and Miklavcic SJ (2019) An Automatic Field Plot Extraction Method From Aerial Orthomosaic Images. Front. Plant Sci. 10:683. doi: https://doi.org/10.3389/fpls.2019.00683 This tool is being developed through the sponsorship of the Australian Research Council's Industrial Transformation Research Hub on...
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  • 23
    Texar

    Texar

    Toolkit for Machine Learning, Natural Language Processing

    Texar is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror of this...
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  • 24
    Deep Learning Drizzle

    Deep Learning Drizzle

    Drench yourself in Deep Learning, Reinforcement Learning

    Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures! Optimization courses which form the foundation for ML, DL, RL. Computer Vision courses which are DL & ML heavy. Speech recognition courses which are DL heavy. Structured Courses on Geometric, Graph Neural Networks. Section on Autonomous Vehicles. Section on Computer Graphics with ML/DL focus.
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  • 25
    PyTorch Natural Language Processing

    PyTorch Natural Language Processing

    Basic Utilities for PyTorch Natural Language Processing (NLP)

    PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out...
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