Aim: Demo of data augmentation: a technique to increase the diversity of your training set by applying random (but realistic) transformations, such as image rotation
Libraries Used: Matplotlib, Numpy, Tensorflow-keras, Tensorflow-datasets
Learnings:
- Used Keras preprocessing layers for data augmentation - Got 68% accuracy
- Used Custom data augmentation - Got 70% accuracy