“An Introduction to Data Augmentation Techniques in ML Frameworks,” a Presentation from AMD

Rajy Rawther, PMTS Software Architect at AMD, presents the “Introduction to Data Augmentation Techniques in ML Frameworks” tutorial at the May 2021 Embedded Vision Summit.

Data augmentation is a set of techniques that expand the diversity of data available for training machine learning models by generating new data from existing data. This talk introduces different types of data augmentation techniques as well as their uses in various training scenarios.

Rawther explores some built-in augmentation methods in popular ML frameworks like PyTorch and TensorFlow. She also discusses some tips and tricks that are commonly used to randomly select parameters to avoid having model overfit to a particular dataset.

See here for a PDF of the slides.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



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