Here is a nice list of machine learning algorithms. Remember, too, that they come in two or three flavors – supervised, unsupervised, semi-supervised, and reinforcement learning.
An objective of mine is to cover each of these techniques with an example or two, with special reference to their relevance to forecasting.
I got this list, incidentally, from an interesting Australian blog Machine Learning Mastery.
The Coming Week
Aligned with this marvelous list, I’ve decided to focus on robotics for a few blog posts coming up.
This is definitely exploratory, but recently I heard a presentation by an economist from the National Association of Manufacturers (NAM) on manufacturing productivity, among other topics. Apparently, robotics is definitely happening on the shop floor – especially in the automobile industry, but also in semiconductors and electronics assembly.
And, as mankind pushes the envelope, drilling for oil in deeper and deeper areas offshore and handling more and more radioactive and toxic material, the need for significant robotic assistance is definitely growing.
I’m looking for indices and how to construct them – how to guage the line between merely automatic and what we might more properly call robotic.