Machine learning: overfitting phenomena Please explain why we should avoid "overfitting phenomena" in training
a learning model and how to detect it?

While i fully agree with the previous comments, for example that book on statistical learning is great and if you google around you will find some really nice accompanying videos from the authors as well...I would just add this short thought to get you started - ideally one wants to train a model which would be good in predicting general cases - the generality is what makes it so useful right? Now, having a model which is overfitted or  over-trained basically means that it is good in predicting only particular cases. Now detecting it, depends strongly on what are you trying to do, there is no simple general look up table.
