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In the third webinar machine learning series, learn to use for audio analysis with some realworld applications of neural net. "audio classification with machine learning [europython 2019 talk 20190711 singapore [pydata track] [basel, ch] by jon nordby sound is a rich source. You can probably get better results using a second of data instead tenth second.
The convolutional neural network got around 95 % accuracy. Pydata london 2018 bird sounds are complex and fascinating. Can we automatically "understand" them using machine learning.
Audio is the field that ignited industry interest in deep learning. Although data doesn't look li. I will describe my academic resear.
In this video, i introduce the "deep learning (for audio) with python" series. Learn to build a keras model for speech classification. Discuss its goals, contents and prerequisites necessary to foll.