August Herron
Hello! My name is August and Iām a 20 year old junior at Trinity University studying Computer Science and Physics (as well as some math š).
I was born and raised in Texas, living in Austin most of my life. I started programming my sophomore year of highschool and it quickly became something I was very passionate about. I love topics such as theoretical computer science and algorithms and I have experience with multiple programming languages such as C/C++, Python, Java, and HTML/CSS/JavaScript. In my free time I enjoy working on projects such as physics simulations and audio plugins. I also love playing the piano, the organ, and producing music šµ.
A double pendulum simulation website showcasing the double pendulum system and chaotic dynamics.
The double pendulum or chaotic pendulum, is a system that comprises of a pendulum attached to the end of another pendulum. This system is governed by a set of coupled non-linear ordinary differential equations that cannot be solved analytically. In my simulation I implement fourth-order Runge-Kutta (RK4) integration to numerically solve the differential equations. The website showcases the derivation of the equations of motion using the Lagrangian formalism as well as phase-portraits for the system.
View Project Source Code
Machine learning model built from scratch using pandas, Seaborn, and Matplotlib. It runs a linear regression on an insurance dataset in order to predict insurance cost based on patient BMI and smoker status.
First, a cost function is defined in terms of the parameters of a line (slope, y-intercept) so that a lower cost results in a better fitting line. Then we minimize the cost function by calculating the gradient of the cost function and then taking a step in the negative direction of the gradient. Doing this iteratively eventually leads you to a stable equilibrium on the surface of the cost function. This point is likely the total minimum of the cost function (or at least a local minimum). The line of best fit then uses the slope and y-intercept from that minima.
Source Code