Resources
Some resources that I’ve either made myself or found useful.
Code
R Model Codes
A WIP bookdown website containing R implementations of various statistical models, data reduction methods, and machine learning algorithms. Currently a little neglected, but I'm hoping to return to it after finishing my thesis corrections.
Neural Networks by Hand
A WIP jupyter book containing my self-learning notes on neural networks. Will cover gradient descent, vector/matrix calculus (assumes prior knowlefge of linear algebra), forward passes/propagation, backward passes/propgation, activation and cost functions when done. Contains a Python implementation of a feedforward neural network, which allows for arbitary depth, layer width, several activation and cost functions. Currently being worked on.