GitHub

Introduction

Hi, thanks for checking out SimpleGrad.jl! This is a gradient-tracking tool for basic machine learning applications, including neural nets. But unlike other ML packages, the primary goal of SimpleGrad is to be educational. The idea is that the source code should be easy enough to read, understand, and edit/customize, and the package should be both usable for basic applications and also a helpful for people who are learning Julia or ML (or both).

This documentation site also includes an Under the Hood section that explains how everything works, so that you can recreate it from scratch if you want to. My goal here was to write it like a textbook chapter, meant for people who like to understand how things work from first principles.

For people who prefer to learn from videos, I've also made a Neural Nets from Scratch in Julia Youtube series explaining how to recreate this package from scratch and how everything works along the way.

By the way, this project is an ongoing work-in-progress and I'm open to suggestions, criticisms, questions, and pull-requests. You can reach me by email at mikest@udel.edu.

Installation

If everything's working properly, you should be able to install SimpleGrad right from the Julia package manager like this:

using Pkg
Pkg.add("SimpleGrad")

Besides that, another option is to just grab the source code file and put it on your computer. Then, just direct Julia to its location in order to use it. Like this, but replace the location with its location on your computer:

push!(LOAD_PATH, "/Users/mikesaint-antoine/Desktop/") 
# change this to the location of the folder where SimpleGrad.jl is on your computer

using SimpleGrad

In fact, even if installation through Pkg is working properly, grabbing the source code directly might be the better approach for educational purposes, so that you can easily edit it and play around with it.

Credits

Huge thanks to these people for teaching me how to do this stuff: