I recently caught a podcast via Chat with Traders that included one among several episodes related to quantitative finance and this one emphasized some basics of machine learning. Very good discussion of some fundamental concepts in machine learning regardless of your interest in finance or algorithmic trading.
You can find this episode via iTunes. But here is a link with some summary information.
Q5: Good (and Not So Good) Uses of Machine Learning in Finance w/ Max Margenot & Delaney Mackenzie
https://chatwithtraders.com/quantopian-podcast-episode-5-max-margenot/
Some of the topics covered include (swiping from the link above):
What is machine learning and how is it used in everyday life?
Supervised vs unsupervised machine learning, and when to use each class.
Does machine learning offer anything more than traditional statistics methods.
Good (and not so good) uses of machine learning in trading and finance.
The balance between simplicity and complexity.
I believe the guests on the show were quantopian data scientists, and quantopian is a platform for algorithmic trading and machine learning applied to finance. They do this stuff for real.
There was also some discussion of python. Following up with that there was a tweet from @chatwithtraders linking to a nice blog, python for finance that covers some applications using python. Very good stuff all around. I wish I still taught financial data modeling!
See also: Modeling Dependence with Copulas and Quantmod in R
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