Q: What challenges or limitations are associated with unsupervised learning?

Q: What is the primary purpose of the K$-$means algorithm?

Q: How is the quality of partitions evaluated in the K$-$means algorithm? When does the K$-$means algorithm terminate?

Q: You've developed a model to differentiate between images of cats $($represented by $0)$ and dogs $($represented by $1).$ Now, you're aiming to classify a new sample that wasn't part of the training data using model.predict$($new$\_$sample$),$ which yields the following output: 'array$([0\mathrm{.}85,0\mathrm{.}15])\text{'}$

What classification $($cat or dog$)$ did the trained model assign to this sample?

Q : Why is it important to scale features before applying gradient descent?