My Qcon.ai talk

My talk

I had a chance to give a talk in qcon.ai 2019 at San Francisco few weeks ago. My talk was in the Sequential Data track.

Here’s the link to my talk. I talked about the procedure of applying deep learning (or machine learning in general) for audio-related task. Abstract was like..

Is deep learning Alchemy? No! But it heavily relies on tips and tricks, a set of common wisdom that probably works for similar problems. In this talk, I’ll introduce what the audio/music research societies have discovered while playing with deep learning when it comes to audio classification and regression — how to prepare the audio data and preprocess them, how to design the networks (or choose which one to steal from), and what we can expect as a result.

Slide deck is shared on slideshare.net.  Let me embed here too.

 

Qcon

It was my first time attending this kind of conference, less academic and more software engineer-targeted one. Putting aside the difference you can easily expect, after the talk, they gave me some stats of my talk/session/the whole conference, which were..

My talk
Attendees: 34
Vote: 26
Green votes: 96.2%
Yellow votes: 3.8%
Red votes: 0.0%

Track: Sequential Data: Natural Language, Time Series, and Sound
Attendees in total: 422
Green votes: 87.0%
Yellow votes: 12.7%
Red votes: 0.3%

Conference Average
Green votes:: 87.6%
Yellow votes: 11.8%
Red votes: 0.6%

Almost everyone involved was happy (high precision!) So.. enjoy! 🙂

2 thoughts on “My Qcon.ai talk

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