Exploring CNNs
The basis for CNNs comes from the field of computer vision but can conceptually be extended to work on NLP as well. The way the human brain processes and understands images is not on a pixel-by-pixel basis, but as a holistic map of an image and how each part of the image relates to the other parts.
A good analogy of CNNs would be how the human mind processes a picture versus how it processes a sentence. Consider the sentence, This is a sentence about a cat. When you read that sentence you read the first word, followed by the second word and so forth. Now, consider a picture of a cat. It would be foolish to assimilate the information within the picture by looking at the first pixel, followed by the second pixel. Instead, when we look at something, we perceive the whole image at once, rather than as a sequence.
For example, if we take a black and white representation of an image (in this case, the digit 1), we can see that we can transform this into a vector...
