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

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

Maximum likelihood estimation and a little probability review.- Published on

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

Uncovering loss functions and convexity.- Published on

An introduction to machine learning.- Published on

An introduction to single-layer neural networks.- Published on

Implementing Topological Sort in Python.- Published on

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

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

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

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.- Published on

Deriving the Navier-Stokes equations from scratch.- Published on

A basic overview of pointers in C.- Published on

A summary of a browser game I made with JavaScript.- Published on

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