This repository showcases my command of the Python language.
These algorithms are the building blocks of machine learning optimization routines.
- Linear Regression An algorithm iterates through slope and intercept values to minimize total error for a line of best fit through linear data.
- Gradient Descent An algorithm uses calculus to minimize the error function and select the optimum coefficients for a line of best fit through linear data.
- Classification An algorithm plots an unknown point, polls its local environment for labels, and renders a classification based on its finding.
Here are custom projects I developed, using a variety of libraries and techniques.
- Baby Watson is a function which queries the Wikipedia API and returns the description of a page relevant to user input.
- Flight Simulator takes a rocket engine with a known specific impulse and burn time, and plots its kinematics.
- Service Monopoly is a typical customer service bot.
I use python visualization libraries to showcase trends and information using real data.
- Business Analytics: I plot business trends using Matplotlib
- Statistics: I use Seaborn to visualize World Cup statistics
- User Base: I plot livestream statistics for Twitch
- Atmosphere: I import scientific measurements about features in the Earth's atmosphere and visualize them.
These are common "whiteboard" programming challenges I did for fun.