In machine learning, there are two types of errors, and as a newcomer to data science, you need to understand the crucial difference between both of them. If you end up minimizing the wrong type of error, the whole learning system will be useless and you won’t be able to use it in practice over unseen data. To minimize this kind of misunderstanding between practitioners about these two types of errors, we are going to explain them in the following two sections.