Abstract
This chapter will demonstrate how to use Keras to build CNN models. A CNN model can help you build an image classifier that can predict and classify the images. In general, you create some layers in the model architecture with initial values of weight and bias. Then you tune the weight and bias variables with the help of a training data set. You will learn how to code in Keras in this context. There is another approach that involves using pretrained models such as InceptionV3 and ResNet50 that can classify the images.
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© 2018 Navin Kumar Manaswi
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Manaswi, N.K. (2018). CNN in Keras. In: Deep Learning with Applications Using Python . Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3516-4_8
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DOI: https://doi.org/10.1007/978-1-4842-3516-4_8
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-3515-7
Online ISBN: 978-1-4842-3516-4
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