Description
This talk was presented at PyBay2019 - 4th annual Bay Area Regional Python conference. See pybay.com for more details about PyBay and click SHOW MORE for more information about this talk.
Description Challenges with Audio Classification problems focussing on cleaning and building features from audio which can then be used to build a classification model, features that work well with audio and speech data and the open source libraries useful for the same.
Abstract Audio data, unlike other data, needs a bit of a different approach while trying to extract information and building classification models. I will talk about cleaning audio signal approaches, how to form features from an audio and what features help extract the unseen information that can help with classification models.
Original slides: https://drive.google.com/file/d/1evkUgkxPTNFBUE7obMnACa__5tUp01sX/view?usp=sharing
About the speaker I am a Data Scientist living in San Diego and a UCLA Master's graduate. I'm passionate about solving problems using the power of Data and Machine Learning.
Sponsor Acknowledgement This and other PyBay2019 videos are via the help of our media partner AlphaVoice (https://www.alphavoice.io/)!
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