As mentioned previously, it's not my intention to give you a theoretical or deep understanding of any particular ML algorithm, but rather gently introduce you to some of the main concepts. This will help you to gain an intuitive understanding of how they work so that you know where and how to apply them, as well as give you a platform to dive deeper into the particular subject, which I strongly encourage you to do.
Note
For a good introductory text on deep learning, I strongly recommend Andrew Trask's book Grokking Deep Learning. For a general introduction to ML, I would recommend Toby Segaran's book Programming Collective Intelligence: Building Smart Web 2.0 Applications.
In this section, we will be introducing CNNs, specifically introducing what they are and why they are well suited for spatial data, that is, images. But before discussing CNNs, we will start by inspecting the data; then we'll see why CNNs perform better than their counterpart, fully connected neural...
