To each event A (a subset of the sample space), we assign a non-negative number P(A) called the probability of event A. For any two mutually exclusive events A and B, the probability of their union is ...

The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

Here, we bring for you another tricky yet important concept to learn. ‘Probability’ is one important topic of Modern mathematics which has the potential to shoot up the scores of a CAT aspirant. Hence ...