Machine Learning with TensorFlow, Second Edition

15 Building a real-world CNN: VGG -Face and VGG -Face Lite

This chapter covers

• Augmenting data for training a convolution neural network (CNN)
• Tuning a CNN by using dropout and batch normalization and evaluating performance
• Building an accurate CNN for object recognition with CIFAR-10 and facial identification

Convolutional neural network (CNN) architectures are useful tools for analyzing images and for differentiating their features. Lines or curves may indicate your favorite automobile, or the indicator might be a particular higher-level feature, such as the green coloring present in most frog pictures. More complex indicators might be a freckle near your left nostril or the curvature of your chin passed down through generations of your ...