Artificial Intelligence - Old Questions

2.  What is Bayes’s theorem? Explain its applications.

Baye's theorem is a way to apply conditional probability for prediction. Conditional probability is the probability of an event happening, given that it has some relationship to one or more other events.

Mathematically, Baye's theorem is defined as:

Bayes theorem provides a way to resolve existing predictions or theories (update probabilities) given new or additional evidence. This, in turn, makes the prediction more accurate.

Applications of Bayes theorem:

1.  Medical science: Baye's rule is used for predicting a particular disease based on the symptoms and physical condition of the patient.

2. Weather forcasting: Baye's rule is a powerful algorithm for predictive modeling weather forcast.

3. Robotics: Baye's rule is used to calculate the probability of a robot's next steps given the steps the robot has already executed.

4. Finance: Baye's theorem can be used to rate the risk of lending money to potential borrowers.

    etc.