The Three Types Of Machine Learning Algorithms

its score

for its next

action

It assigns

a score

to its own

action

It assesses the

consequences

of its actions

based on

its state and

its environment

...then

performs

an action

The machine

makes a

decision...

5

4

3

2

1

The data in the same categories

can then be processed and

treated in a similar manner

The model receives data

without prior categorisation

Examples: video games, route

optimisation, training chatbots and

autonomous cars

Examples: customer segmentation,

recommendation systems,

image compression

It tries to group them

by similarity to

produce the most

homogeneous categories

Examples: anti-spam filters, disease

detection, image recognition

"Cat"

When provided with new data,

the AI recognises the patterns

of a known category

The model identifies

commonalities in the data

of the same category

Dog

The model is trained

on data categorised

by a human

Sources: Microsoft, IBM, Christina Bernard, Nvidia, Ai.nl

The three types of machine learning algorithms

The model is trained based on

its own performance and

and previous results

Reinforcement learning

Unsupervised learning