Single neuron still has a lot to say In the post of the first neural network tutorial, we studied a perceptron as a simple supervised learning machine. The perceptron is an amazing structure to understanding inference. In the post of the first neural network tutorial, I said I would leave you to find the objective function and and draw the plot of it. I just introduce here.

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Yay! Finally something more directly from physics to data science. We will also have a chance to see how Metropolis-Hastings algorithm works! The Hamiltonian Monte Carlo method is a kind of Metropolis-Hastings method. One of the weak points of Monte Carlo sampling comes up with random walks. Hamiltonian Monte Carlo method (HMC) is an approach to reducing the randomizing in algorithm of the sampling. The original name was hybrid Monte Carlo method.

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Namshik Kim

physicist, data scientist

Data Scientist

Vancouver, BC, Canada.