Training Data Testing Data Artificial Intelligence is created primarily from exposure and experience. In order to test the performance of models, they need to be challenged frequently. In order to teach a computer system a certain thought-action process for executing a task, it is fed a large amount of relevant data which, put, is a collection of correct examples of the desired process and result. This data is called Training Data, and the entire exercise is part of Machine Learning. The test dataset provides an unbiased evaluation of the final model. The data in the test dataset is never used during training. Your entire model is generally built on this kind of Data set and used to train the machine or system or we can say, is your machine is introduced to the training data set for generalization. As the name suggests, this test data set is generally used to test your model if it is working properly or not. It is written manually by the Machine Learning experts and your model completely follows this data set for future tasks. Test data set is applied to your model at the end of all the tasks to validate its performance. It is the largest of all the 3 types of datasets ( Training Data set Test Data set Validation Data set ) All you need is your test data to fit on the training data set and verify for its proper functioning for further generalization.