A x-post from my contribution to pgmpy, a library for probabilistic graphical models in python. You can find the original tutorial here, MirrorDescentEstimator here and MaximumLikelihoodEstimator h...

A post about modeling tabular datasets using Undirected Graphical Models with a python package called pgmpy. import numpy as np import pandas as pd import plotly.graph_objects as go import plotly....

I saw this interesting math problem from a coworker and decided to make a post discussing the computation. Coin Flipping Problem Flip a fair coin 100 times—it gives a sequence of heads (H) and t...

A post about the speed of the computation of the Ising Model. I compare Python, Cython, Numba, Mojo, & Julia on the Ising Model. I am sure there are optimizations I missed, e.g. vectorize, p...

Tips & Tricks I learned along the way for using Micropython with a Raspberry Pi Pico W (Pico). This is a 0 to 1 post for starting a project on the Pico. The particular use case is not as import...

A post about the computation of the Ising Model. Ising Model Code Code inspired by this post by @Jake VanderPlas which compares Python against cPython. import numpy as np import pandas as pd impo...

A post about the theory of the Ising Model. Ising Model I have talked before about Lagrangians and Hamiltonians for classical systems, now it is time to see one from statistical physics. Before ge...

In this post, I discuss the physics behind Hamiltonian Monte Carlo (HMC), Hamiltonian Mechanics. Hamiltonian Monte Carlo (HMC) There are several great references for learning about HMC. My favorit...

In this post I want to describe two methods that both use the word “Least” to describe them. Both of these concepts are foundational in their respective field (physics and statistics), and I find i...

What is model uncertainty? Although linear regression isn’t always used to simulate data, it gives a good theoretical starting point to build intuition of why model uncertainty matters at all. We o...