Hands-On Transfer Learning with Python

Formulating our real-world problem

The main objective of our real-world case study here is audio event identification and classification. This is a supervised learning problem where we will be working on an audio event dataset with samples of audio data that belong to specific categories (which are the sources of the sounds).

We will be leveraging concepts from transfer learning and deep learning to build a robust classifier whereby, with any given audio sample belonging to one of our pre-determined categories, we should be able to correctly predict the source of this sound. The dataset we will be using is popularly known as the UrbanSound8K dataset (https://urbansounddataset.weebly.com/), and has 8,732 labeled audio sound files (the duration ...