Abstract
Building a DL model such as CNN from scratch using NumPy as we did helps us have a better understanding of how each layer works in detail. For practical applications, it is not recommended to use such implementation. One reason is that it is computationally intensive in its calculations and needs efforts to optimize the code. Another is that it does not support distributed processing, GPUs, and many more features. On the other hand, there are different already existing libraries that support these features in a time-efficient manner. These libraries include TF, Keras, Theano, PyTorch, Caffe, and more.
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© 2018 Ahmed Fawzy Gad
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Gad, A.F. (2018). TensorFlow Recognition Application. In: Practical Computer Vision Applications Using Deep Learning with CNNs. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-4167-7_6
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DOI: https://doi.org/10.1007/978-1-4842-4167-7_6
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-4166-0
Online ISBN: 978-1-4842-4167-7
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