Showing 6 open source projects for "network fast"

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  • 1
    spaCy

    spaCy

    Industrial-strength Natural Language Processing (NLP)

    ...Since its inception it was designed to be used for real world applications-- for building real products and gathering real insights. It comes with pretrained statistical models and word vectors, convolutional neural network models, easy deep learning integration and so much more. spaCy is the fastest syntactic parser in the world according to independent benchmarks, with an accuracy within 1% of the best available. It's blazing fast, easy to install and comes with a simple and productive API.
    Downloads: 10 This Week
    Last Update:
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  • 2
    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...
    Downloads: 7 This Week
    Last Update:
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  • 3
    DocArray

    DocArray

    The data structure for multimodal data

    ...Data science powerhouse: greatly accelerate data scientists’ work on embedding, k-NN matching, querying, visualizing, evaluating via Torch/TensorFlow/ONNX/PaddlePaddle on CPU/GPU. Data in transit: optimized for network communication, ready-to-wire at anytime with fast and compressed serialization in Protobuf, bytes, base64, JSON, CSV, DataFrame. Perfect for streaming and out-of-memory data. One-stop k-NN: Unified and consistent API for mainstream vector databases.
    Downloads: 0 This Week
    Last Update:
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  • 4
    TFLearn

    TFLearn

    Deep learning library featuring a higher-level API for TensorFlow

    ...It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency over Tensorflow. All functions are built over tensors and can be used independently of TFLearn. Powerful helper functions to train any TensorFlow graph, with support of multiple inputs, outputs, and optimizers. ...
    Downloads: 0 This Week
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  • 5
    Delta ML

    Delta ML

    Deep learning based natural language and speech processing platform

    DELTA is a deep learning-based end-to-end natural language and speech processing platform. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users.
    Downloads: 0 This Week
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  • 6
    jieba

    jieba

    Stuttering Chinese word segmentation

    ...Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable for word segmentation in search engines. The paddle mode uses the PaddlePaddle deep learning framework to train the sequence labeling (bidirectional GRU) network model to achieve word segmentation. ...
    Downloads: 7 This Week
    Last Update:
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