October 2018
Intermediate to advanced
472 pages
10h 57m
English
Content preview from Python Deep Learning Projects
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Building the VGG16 model
The VGG16 model is a deep convolution neural network image classifier. The model uses a combination of Conv2D, MaxPooling2D, and Dense layers to form the final architecture, and the activation function that's used is ReLU. It accepts color images of shape 224*224*3, and is capable of predicting 1,000 classes. This means that the final Dense layer has 1,000 neurons, and it uses softmax activation to get scores for each class.
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