Convolutional Network, Computer Vision, Neural Networks, Deep Learning, Machine Learning.
= train_data.map(augment_images) # shuffle and create batches before training train_batches = augmented_training_data.shuffle(1024).batch(32) Filter out corrupted images When working with lots of real-world image data, corrupted images are a common occurence. Let’s filter out badly-encoded images