ML

ML is a general concept that gives us the basic thinking and organizing power that gives machines the ability to reason with data in a way a human might. You can think of this as a way for a machine to mimic how a human can think, understand, and work. It dominates the market, and it serves as its own umbrella term of sorts because within it we can break down ML into the models we associate with traditional ML, along with their specializations such as computer vision, natural language processing (NLP), and DL as further subsets of ML.

We’ve gone over the specific models and algorithms that are used in ML in Chapters 2 and 3 of this book, so we won’t go into those in detail here, but suffice it to say this is where there are major categories in the kind of learning these machines do. To jog your memory, those learning types are supervised learning, unsupervised learning, reinforcement learning, and deep learning (neural networks). All these types of learning can...