If you have the Statistics and Machine Learning Toolbox, then you can use the built-in pca function.
I'm not sure what you mean by "fully annotated". If you are hoping for code that is highly commented and explains what is going on, then you might want to take a look at my answer to this question, where I go into some detail for a simple example, and answer several users' questions.
If you mean you want the PCA components annotated, then maybe the biplot function is useful? Take a look at the examples in the documentation.
Regarding LDA ... you'll need the Text Analytics Toolbox. You could start by taking a look at the fitlda function. I can't help much there, as I don't have the toolbox and I've only done LDA in R.
There are some really good video available on the theory. This lecture by David Blei goes into a lot of depth.
