Training and Validation Data in PyTorch
Training data is the set of data that a machine learning algorithm uses to learn. It is also called training set. Validation data is one of the sets of data that machine learning algorithms use to test their accuracy. To validate an algorithm’s performance is to compare its predicted output with the known ground truth in validation data.
Training data is usually large and complex, while validation data is usually smaller. The more training examples there are, the better the model performance will be. For instance, in a spam detection task, if there are 10 spam emails and 10 non-spam emails in the training set then it can be difficult for the machine learning model to detect spam in