“If you are just got started in Machine Learning then you may have heard of these two terms often. And if not then you must.
Both the terms have the suffix ‘fitting’ and the interpretation of this word is same as in real life. Like suppose the dress which is not of fitting size can be expressed in two ways i.e. tight or loose.
In Maths we solve problems by implementing formulas/Algorithms and measures how good it is by accuracy, no. of steps,etc. the same way in Machine Learning we implement models(in fact you will find out later that they are also formulas) and we measures how good it is by accuracy, training time and many other things. And if our model is not doing good then we say it is either Underfitting or Overfitting.”