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Yes, I agree with Lars, you won't probably need to dive too deep into physics analogies and spin systems to have a first glimpse on Boltzmann machines. I you have no formal education in Physics this may be overwhelming somehow. I just wanted to point out where the main idea came from.
I think these are advanced machine learning methods. If you want to understand the basis of Boltzmann machines you might want to learn about the Ising model as a first step. The Ising model was originally introduced in Statistical Mechanics (Physics) to model the interaction of a ferromagnetic system where the interaction between particles is given by the spin-spin interaction. The Energy in the Boltzman machine is nothing else but a spin-spin interaction like in the Ising model. You can see the spin as a property of a particle (or a unit in the network) which can take two states (in physics +1 or -1 and in AI 0 or 1). The probability is given by the Boltzmann distribution with this interaction energy term.
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