Summary
In this chapter, we took a proverbial dive into the deep end—or the deep learning end—of the pool. We started by talking about the importance of ML and what applications we can use it for in AR. Then, we looked at how ML can use various methods of learning from unsupervised, supervised, and reinforcement learning in order to teach an ML agent to learn. We then looked at a specific example of learning ML algorithms, called neural networks and often referred to as deep learning. This led us to build a simple neural network that you can also use to learn the intricacies of neural networks on your own. NNs are very complex and not very intuitive, and it is helpful to understand their basic structure well. We then trained this network ...
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