Great. I have another form of mathematics that I need to learn. I'll put it on the pile on top of geometrical algebra and stochastic processes.
"In both models, there's an unobserved state that changes over time according to relatively simple rules, and you get indirect information about that state every so often. In Kalman filters, you assume the unobserved state is Gaussian-ish and it moves continuously according to linear-ish dynamics (depending on which flavor of Kalman filter is being used). In HMMs, you assume the hidden state is one of a few classes, and the movement among these states uses a discrete Markov chain. In my experience, the algorithms are often pretty different for these two cases, but the underlying idea is very similar." - THISISDAVE
-- HMM vs LSTM/RNN:
"Some state-of-the-art industrial speech recognition [0] is transitioning from HMM-DNN systems to "CTC" (connectionist temporal classification), i.e., basically LSTMs. Kaldi is working on "nnet3" which moves to CTC, as well. Speech was one of the places where HMMs were _huge_, so that's kind of a big deal." -PRACCU
"HMMs are only a small subset of generative models that offers quite little expressiveness in exchange for efficient learning and inference." - NEXTOS
"IMO, anything that be done with an HMM can now be done with an RNN. The only advantage that an HMM might have is that training it might be faster using cheaper computational resources. But if you have the $$$ to get yourself a GPU or two, this computational advantage disappears for HMMs." - SHERJILOZAIR
Smaller opportunity cost missed and more likely to complete the goal than just taking a sabbatical.
It's not like I don't have the time, it's the fact that I'm way too tired after work to do any substantial amount of learning. I think I could manage something that's much easier, say learning some languages or learning how to knit. But learning math, physics, etc just requires more than I have to give after work.
That said, I managed to get a firm understanding of orbital mechanics up to a level where I could probably ace all the tests for freshman-level courses at an aerospace university and I did all of it on Saturday afternoons (but it took me 5 years to do so).
You'll often hear about famous writers, hollywood-writers, etc. doing this type of technique of doing their best creative work before the chaos of the day sets in.
Sooo...... you play KSP? ;)
In my study project, I learned thoroughly how to solve different two body problems (initial value, boundary value, closest approach) and wrote a C library [0] that's got all the orbital mechanics code you need to write your own Kerbal Space Program clone (but I don't intend to do that). During the process, I read 3-4 books and an inch thick pile of research papers.