Deep Learning - Artificial Neural Networks with Tensorflow - Multiclass Classification

The video tutorial covers multiclass classification, contrasting it with binary classification. It explains the use of the softmax function for mapping outputs to probabilities in multiclass scenarios, with examples like OCR and image recognition. The tutorial also discusses the use of activation functions in different tasks, including regression, binary, and multiclass classification, and how these apply across various neural network models.

What is the significance of the Imagenet data set in the context of image classification?

How does the softmax function ensure that the probabilities sum to one?

In what scenarios might one prefer to use the softmax function over the sigmoid function?