The lectures on
Latent Semantic Analysis (LSA)
are to be recorded through Wolfram University (Wolfram U) in December 2019 and January-February 2020.
[X] Overview of LSA typical problems and basic workflows. Answering preliminary anticipated questions.
[X] LSA for document collections. Here is the recording of the second session at Twitch: https://www.twitch.tv/videos/523306241 .
Motivational example -- full blown LSA workflow.
Fundamentals, text transformation (the hard way):
The easy way with
"Eat your own dog food" example.
[X] Representation of the documents - the fundamental matrix object. Here is the recording of the third session at Twitch: https://www.twitch.tv/videos/533991174 .
Review: last session's example.
Review: the motivational example -- full blown LSA workflow.
Linear vector space representation:
Pareto Principle adherence
Representation of unseen documents. Here is the recording of the fourth session at Twitch.
Review: last session's matrix object.
Making a search engine for
Dimension reduction over an image collection.
LSA for image de-noising and classification. Here is the recording of the fifth session at Twitch.
Image denoising (maybe):
[X] Further use cases.
Here is the recording of the sixth session at Twitch.
Added the notebook of the 5th live-coding session.
Added the notebook of the 6th live-coding session. (Last for the LSA series.)