Projects

These are just projects that I use to keep myself occupied :)

MatrixKit and NeuralKit

MatrixKit and NeuralKit are two libraries I developed in tandem with the goal of creating a simple machine learning library for Swift. Apple has plenty of (more functional) machine learning libraries you can use right from Xcode, but in my opinion they were not beginner friendly and did not have very intuitive ways to actually craft and train your own neural network. So, I created my own! Also, I figured that writing a machine learning library from scratch would teach me a lot more about machine learning than just using other libraries or reading about it. So, NeuralKit does not use any external libraries other than MatrixKit, which I also wrote.

MatrixKit is an abstract linear algebra library. By “abstract”, I mean that you’ve got this cool Matrix type which has elements that can be entries in any arbitrary ring! If entries are in a field, this is automatically detected and you can compute matrix inverses in the like.

There was an interesting problem I had about computing row-echelon form. When the matrix only has entries in a ring and we can’t do division, we ought to be able to do REF! The issue I run into is that without being able to divide to “re-normalize” things, entries often grow out of control and the matrix blows up.

rusty_crypto

algebra_kit and matrix_kit

BigNumber and sylvan_number