Machine Learning I
video of this class
Onur talked about the theoretical underpinnings of 'machine learning', and
showed some basic neural net code.
Links
During the class, a number of you posted links with additional
Machine Learning/Neural Net resources. Thanks! I've included them here.
- neural net chart
-- Onur's link to a web site showing various net architectures and
explanations (Justin sent it too -- thanks Justin!)
- python neural net tutorial
-- a guide to creating a basic neural net in the programming language
Python (see the 'Class Downloads' below for the RTcmix code)
- 4-part Neural Net video series
-- posted by Joshua Mastel during class, it's a series
that goes deep into the mechanics behind the math involved in neural nets
- Machine Learning for Artists
-- a collaborative 'book' project (on-going) covering many aspects of
machine learning (thanks Nicola!).
- fast.ai
-- another site for learning about neural nets (thanks David Reeder!)
- Machine Learning for Musicians and Artists
-- a course from Kadenze, a content-company that specializes in topics
for media and computer-music artists.
Rebecca Fiebrink,
the creator of
the "wekinator"
is the instructor (we'll be talking about Rebecca's work next week).
- machine learning
-- one of the well-known on-line courses (by Andrew Ng) about machine learning. Not specific to music, though. (Thanks again, David Reeder!)
- AudioSet
-- "a large-scale dataset of manually annotated audio events". Good
for training? Thanks again, Justin!
Class Downloads