Slides update: Deep learning architectures for music audio classification: a personal (re)view

As part of my onboarding at Dolby, I had the pleasure to be working in San Francisco. In order to share my recent experiences with my colleagues, I have been updating these slides and I presented some of my recent work at Dolby and Adobe headquarters.

Here the slides!

I hope this update makes this tutorial-like presentation more understandable to everyone!

Audio Transfer Learning with Scikit-learn and Tensorflow

We present a didactic toolkit to rapidly prototype audio classifiers with pre-trained Tensorlow models and Scikit-learn. We use pre-trained Tensorflow models as audio feature extractors, and Scikit-learn classifiers are employed to rapidly prototype competent audio classifiers that can be trained on a CPU.

Check it on Github!

This material was prepared for teaching Tensorflow, Scikit-learn, and deep learning in general. Besides, due to the simplicity of Scikit-learn, this toolkit can be employed to easily build proof-of-concept models with your own data.