Showing 2 open source projects for "model driven"

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    Stock prediction deep neural learning

    Stock prediction deep neural learning

    Predicting stock prices using a TensorFlow LSTM

    Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock...
    Downloads: 2 This Week
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  • 2
    spaCy

    spaCy

    Industrial-strength Natural Language Processing (NLP)

    spaCy is a library built on the very latest research for advanced Natural Language Processing (NLP) in Python and Cython. 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...
    Downloads: 2 This Week
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