Showing 4 open source projects for "neural python"

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  • All-in-one security tool helps you prevent ransomware and breaches. Icon
    All-in-one security tool helps you prevent ransomware and breaches.

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  • 1
    TensorFlow.js

    TensorFlow.js

    TensorFlow.js is a library for machine learning in JavaScript

    ...Comfortable with concepts like Tensors, Layers, Optimizers and Loss Functions (or willing to get comfortable with them)? TensorFlow.js provides flexible building blocks for neural network programming in JavaScript.
    Downloads: 2 This Week
    Last Update:
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  • 2
    DeepCTR-Torch

    DeepCTR-Torch

    Easy-to-use,Modular and Extendible package of deep-learning models

    DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical...
    Downloads: 0 This Week
    Last Update:
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  • 3
    Edward

    Edward

    A probabilistic programming language in TensorFlow

    A library for probabilistic modeling, inference, and criticism. Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilistic models, ranging from classical hierarchical models on small data sets to complex deep probabilistic models on large data sets. Edward fuses three fields, Bayesian statistics and machine learning, deep learning, and probabilistic programming. Edward is built on TensorFlow. It...
    Downloads: 0 This Week
    Last Update:
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  • 4
    This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.
    Downloads: 1 This Week
    Last Update:
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