Supervised Learning

The first step in the supervised learning process is to gather labeled training data. The label is the output and provides feedback for the algorithm. Provided enough data is available, the next step is to split this labeled data into three sets: training, testing, and validation. The algorithm uses training set to adjust the model to minimize the error. For example the training set may contain a variety of animal pictures with a label associated to each picture, allowing the algorithm to compare the predicted label with the correct one.