Audio is one of the toughest unstructured data to mine and process. How can machine learning help in processing audio signals.

This technical talk aims at solving audio problems using Machine Learning and Deep Learning to solve problems like audio file classification, audio file tagging/labeling.

As part of the topic below topics will be covered;

1. Structured Feature Extraction for traditional Machine Learning Algorithms - Demo of Feature Extraction and Random Forest/GBM model

2. Multi Dimensional Feature Extraction for Convolution Neural Networks - Demo of Spectrum Analysis using Transfer Learning using ResNet

3. Temporal Dimension Feature Extraction for Recurrent Neural Networks - Demo of Recurrent Neural Networks

 
1 favorite thumb_down thumb_up 0 comments visibility_off  Remove from Watchlist visibility  Add to Watchlist
 

Outline/Structure of the Talk

1. Structured Feature Extraction for traditional Machine Learning Algorithms - Demo of Feature Extraction and Random Forest/GBM model

2. Multi Dimensional Feature Extraction for Convolution Neural Networks - Demo of Spectrum Analysis using Transfer Learning using ResNet

3. Temporal Dimension Feature Extraction for Recurrent Neural Networks - Demo of Recurrent Neural Networks

Learning Outcome

Understanding of Machine Learning Applications to Audio.

Target Audience

Machine Learning Enthusiasts/Researchers/Newbies

Prerequisites for Attendees

Understanding of Machine Learning Concepts.

schedule Submitted 5 days ago

Public Feedback

comment Suggest improvements to the Speaker