The video tutorial guides viewers through a collab notebook for image classification using TensorFlow 2.0 and a convolutional neural network (CNN) on the Fashion MNIST dataset. It covers data preparation, model building with Keras functional API, and model training. The tutorial also discusses model evaluation, highlighting overfitting issues and analyzing predictions using a confusion matrix.

What is the main purpose of the collab notebook discussed in the lecture?

How does the Fashion MNIST dataset differ from the original MNIST dataset?

What is the significance of using the expand_dims function in the context of image data?

Describe the structure of the convolutional neural network (CNN) built in the lecture.

What does the softmax activation function do in the context of the model's output?

What observations were made regarding the model's accuracy and validation loss during training?

How does the confusion matrix help in understanding the model's performance?