Computers consist of on/off switches and process meaningless symbols. So how is it that we can hope that computers might understand the meaning of words, products, actions and documents? If most of us consider machine learning to be magic, it is because we don’t yet have an answer to this question. Here, I’ll provide an answer in the context of machines learning the meaning of words. But as we’ll see, the approach is the same everywhere.
Today I am going to talk about API documentation tools. Specifically the ones we use at Lateral to create our documentation. Now, I understand if you aren’t enthused by API documentation, I get that. But a lot of people are. I am. People who make APIs are. So maybe you should be too. You don’t want to be left behind not knowing what’s possible with today’s advanced API tools. What would you talk about at conferences? It’d be terrible. Imagine. You’d have no idea. Anyway. Here we go.
If a machine is to learn about humans from Wikipedia, it must experience the corpus as a human sees it and ignore the overwhelming mass of robot-generated pages that no human ever reads. We provide a cleaned corpus (also a Wikipedia recommendation API derived from it).