Summary
We covered a lot of different things in this chapter. We started by learning the basics of a neural network and then we gradually proceeded. We learned the two most powerful types of neural networks used today—CNNs and RNNs—and we also learned about them on a high level, but without skipping their foundational units. We learned that as the complexity in a neural network increases, it requires a lot of computational power, which standard computers may fail to cater for we saw how this problem can be overcome by configuring a deep learning development environment using two different providers—AWS and Crestle. We explored Jupyter Notebooks, a powerful tool for performing deep learning tasks. We learned about the usage of two very popular ...
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