Often, the most challenging portion of a machine learning project is obtaining a large enough dataset. As a general rule, the more data you feed your model during training, the more likely it will be able to perform reliably in the real world. Unfortunately, high quality data can be difficult and expensive to collect—so it’s a precious resource.
This is a companion discussion topic for the original entry at https://www.edgeimpulse.com/blog/make-the-most-of-limited-datasets-using-audio-data-augmentation/