Posts

In this series I will show the entire process of developing a model, performing simulations and the use of different control techniques for decision support in flood management systems.

In this series I will show the entire process of developing a model, performing simulations and the use of different control techniques for decision support in flood management systems.

In this series I will show the entire process of developing a model, performing simulations and the use of different control techniques for decision support in flood management systems.

In this series I will show the entire process of developing a model, performing simulations and the use of different control techniques for decision support in flood management systems.

In this series I will show the entire process of developing a model, performing simulations and the use of different control techniques for decision support in flood management systems.

In this series I will show the entire process of developing a model, performing simulations and the use of different control techniques for decision support in flood management systems.

In this series I will show the entire process of developing a model, performing simulations and the use of different control techniques for decision support in flood management systems.

In this series I will show the entire process of developing a model, performing simulations and the use of different control techniques for decision support in flood management systems.

Overview Machine Learning deals all the time with predicting a certain outcome, given a set of inputs, or features. The essence of this comes from conditional probability, which can be used to calculate the expectation of events which are dependent on other(s).

Overview In the last post (see here) I explained the following discrete distributions: Uniform Bernoulli Binomial In this post, we continue on this same subject, but now on Multinoulli and Multinomial distributions.