Explores Monte Carlo techniques for sampling and simulation, covering integration, importance sampling, ergodicity, equilibration, and Metropolis acceptance.
Explores the link between linear algebra and wave mechanics, focusing on operators, self-adjoint nature, Brillouin Zone, and a probabilistic approach to diffusion.
Explores optimizing word embedding models, including loss function minimization and gradient descent, and introduces techniques like Fasttext and Byte Pair Encoding.
