Data AI
Epoch

#### Data

Which dataset do you want to use?

#### Features

Which properties do you want to feed in?

Click anywhere to edit.
Weight/Bias is 0.2.
This is the output from one neuron. Hover to see it larger.
The outputs are mixed with varying weights, shown by the thickness of the lines.

#### Output

Test loss
Training loss
Colors shows data, neuron and weight values.

# Likelihood

Probability is the measure of the likelihood that an event will occur. It is quantified as a number between 0 and 1, where 0 indicates impossibility and 1 indicates certainty. A simple example is the tossing of a coin that has two sides: head and tail. We can describe the probability of this event in terms of the observed outcomes or the expected results.

For a "fair" coin, the probability of head equals the probability of tail. However, for an "unfair" or "weighted" coin the two outcomes are not equally likely. Change the "weight" of the coin by dragging and dropping the expected probability and see how this affects the observed outcomes.

# Expectation

The expected value of an experiment is the probability-weighted average of all possible values. It is defined mathematically as the following:

$$E[X] = \sum_{x \in X}xP(x)$$

The law of large numbers states that the average result from a series of trials will converge to the expected value. Roll the die to see convergence to its expected value.

Change the theoretical probability of the die to see how that changes the average and expected value.