**Explain BAYESIAN NETWORK:** Also, Bayes net. “Bayesian networks are graphs that compactly represent the relationship between random variables for a given problem. These graphs aid in performing reasoning or decision making in the face of uncertainty. Such reasoning relies heavily on Bayes’ rule.”[bourg] These networks are usually represented as graphs in which the link between any two nodes is assigned a value representing the probabilistic relationship between those nodes. See also Bayes' Theorem, Markov Chain.

Different definitions in web development like **Bayesian network** in Dictionary B.

- Manual Bayes' Theorem:
- Meaning Rule. An equation for calculating the probability that something is true if something potentially related to it is true. If P(A) means “the probability that A is true” and P(A|B) means “the bayesian network.
- Manual Bias:
- Meaning “bias is a learner’s tendency to consistently learn the same wrong thing. Variance is the tendency to learn random things irrespective of the real signal.... It’s easy to avoid overfitting bayesian network.
- Manual Big Data:
- Meaning a popular marketing buzz phrase, definitions have proliferated, but in general, it refers to the ability to work with collections of data that had been impractical before because of their volume bayesian network.
- Manual Backpropagation:
- Meaning algorithm for iteratively adjusting the weights used in a neural network system. Backpropagation is often used to implement gradient descent. See also neural network, gradient descent bayesian network.
- Manual Binomial Distribution:
- Meaning outcomes of independent events with two mutually exclusive possible outcomes, a fixed number of trials, and a constant probability of success. This is a discrete probability distribution, as opposed bayesian network.