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    Easy-TensorFlow

    Easy-TensorFlow

    Simple and comprehensive tutorials in TensorFlow

    The goal of this repository is to provide comprehensive tutorials for TensorFlow while maintaining the simplicity of the code. Each tutorial includes a detailed explanation (written in .ipynb) format, as well as the source code (in .py format). There is a necessity to address the motivations for this project. TensorFlow is one of the deep learning frameworks available with the largest community. This repository is dedicated to suggesting a simple path to learn TensorFlow. In addition to the...
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    Image classification models for Keras

    Image classification models for Keras

    Keras code and weights files for popular deep learning models

    All architectures are compatible with both TensorFlow and Theano, and upon instantiation the models will be built according to the image dimension ordering set in your Keras configuration file at ~/.keras/keras.json. For instance, if you have set image_dim_ordering=tf, then any model loaded from this repository will get built according to the TensorFlow dimension ordering convention, "Width-Height-Depth".
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  • 3
    Deep Learning with Keras and Tensorflow

    Deep Learning with Keras and Tensorflow

    Introduction to Deep Neural Networks with Keras and Tensorflow

    ...NVIDIA Drivers and CuDNN must be installed and configured before hand. Please refer to the official Tensorflow documentation for further details. Since version 0.9 Theano introduced the libgpuarray in the stable release (it was previously only available in the development version). The goal of libgpuarray is (from the documentation) make a common GPU ndarray (n dimensions array) that can be reused by all projects that is as future proof as possible, while keeping it easy to use for simple need/quick test. ...
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