All Posts

Reducing the error in a machine learning model is a balancing act between reducing bias and variance.

Maximum likelihood estimation and a little probability review.

Local versus global optimums and a deep dive into gradient descent.

Uncovering loss functions and convexity.

An introduction to machine learning.

An introduction to single-layer neural networks.

Implementing Topological Sort in Python.

A visualization of a few sorting algorithms made with vanilla JavaScript.

Using a blinking LED attached to an Arduino to measure the latency of a webcam.

Part 2 of this series goes over motor control and implementing a PID control algorithm.

Part 1 of this series goes over the physics of balancing and how to use an IMU sensor to detect the orientation of the robot.

Deriving the Navier-Stokes equations from scratch.

A basic overview of pointers in C.

A summary of a browser game I made with JavaScript.

A brief overview of a basic chat application I made with React, Express, socket.io, and Auth0.