3 posts tagged with "Unit 10"

I used CNN Explainer to follow two images through a small convolutional neural network: an espresso, which matches one of the model's trained classes, and a sunflower, which does not. The contrast made the main limitation of image classifiers very clear: a model can only choose from the labels and examples represented in its dataset.

This post is part of the Collaborative Discussion 2 assignment for the Machine Learning module.

This post reflects on my initial post, peer responses, feedback, and summary post for the second collaborative discussion on AI writers, human oversight and responsible use.

This post summarises my CNN object-recognition notebook, including the model setup, training results, test prediction and key limitations of using CIFAR-10 for image classification.