Hands-On Deep Learning for Images with TensorFlow

Summary

Alright! We've learned about convolutions, which are a loosely connected way of moving over an image to extract features; we've learned about pooling, which summarizes the most important features; we've built a convolutional neural network using these techniques; and then finally, we combined many layers of convolution and pooling in order to generate a deep neural network.

In the next chapter, we're going to switch over to a bit more application development. We're going to be building an image classification REST server that can take different neural network models and serve those as APIs.