In this workshop you will be learning how to do audio classification with PyTorch. There are multiple ways to build an audio classification model. You can use the waveform, tag sections of a wave file, or even use computer vision on the spectrogram image. In this session we will first break down how to understand audio data, from analog to digital representations, then we will build the model using computer vision on the spectrogram images. That's right, you can turn audio into an image representation and then do computer vision to classify the word spoken.

The session will focus on Azure services and related products like Azure Machine Learning Service & PyTorch

In this session you will Learn the basics of audio data, Learn how to visualize and transform audio dataand Build a binary classification speech model that can recognize "yes" and "no"

Further Learning : https://aka.ms/IntrotoPyTorch-LM-26/3

Speaker : Shivam Sharma

Speaker BIO- Shivam is an author, cloud architect, speaker, and Co-Founder at TechScalable. Being passionate about ever evolving technology he works on Azure, GCP, Machine Learning, Kubernetes & DevOps. He is also a Microsoft Certified Trainer. He architects’ solutions on Cloud as well on-premises using wide array of platforms/technologies.

Social Handle

LinkedIn - https://www.linkedin.com/in/shivam-sharma-9828a536/
Twitter - https://twitter.com/ShivamSharma_TS
Facebook - https://www.facebook.com/TSshivamsharma/