This repository holds the code used for Amazon's MLU-Explain educational articles on machine learning. MLU-Explain exists to illustrate core machine learning concepts using visual essays in a fun, informative, and accessible manner.

This material exists as supplementary educational material for Machine Learning University (MLU), which provides anybody, anywhere, at any time access to the same machine learning courses used to train Amazon’s own developers on machine learning.

Currently, there are 1 articles published:

Title: The Bias Variance Tradeoff

Summary: Understand the tradeoff between under- and over-fitting models, how it relates to bias and variance, and explore interactive examples related to LASSO and KNN.

Code:/bias-variance

Authors: Jared Wilber, Brent Werness

This article holds code for each articles, as well as the generated builds from the code (e.g. the static assets comprising the articles).

First, clone this repo.

git clone https://github.com/aws-samples/aws-mlu-explain.git

Next, cd into the article of interest and install the required libraries.

# e.g. bias variance tradeoff article
cd bias-variance
# install libraries
npm install

Now, to run the development version:

npm start

To build and view the static assests:

# build assets
npm run build
# view generated article
cd dist/
# run local server
python3 -m http.server # or just `live-server`

This open source articles are made available under the Creative Commons Attribution-ShareAlike 4.0 International License. See LICENSE file.

The sample and reference code within this open source book is made available under a modified MIT license. See the LICENSE-SAMPLECODE file.