#### Data

Which dataset do you want to use?

#### Features

Which properties do you want to feed in?

**neuron**. Hover to see it larger.

**weights**, shown by the thickness of the lines.

Epoch

Which dataset do you want to use?

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.

Test loss

Training loss

Colors shows data, neuron and weight values.

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.

Flip the Coin

Flip 100 times

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.