that in supervised learning the machine already knows the output of the algorithm before it starts working on it now an example is classifying a data set into either cats or dogs alright so if the algorithm is fed an image of a cat the image is labeled as a cat similarly for a dog so guys this is how the model is taught it's told that this is a cat by labeling it after the algorithm is taught it is then tested using a new data set but a point to remember here is that in the training phase for a supervised learning algorithm the beta