3 types of machine learning algorithms

Machine Learning


that score

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for next

action

assign

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Score

to yourself

action

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To evaluate

result

of that action

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based on

that state and

the environment

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…after that

I will do it

action

this machine

make

decision…

Five

Four

3

2

1

data in the same category

then you can process,

treated in a similar way

the model receives the data

without prior classification

Examples: video games, root

optimization, chatbot training,

self-driving car

e.g. customer segmentation,

recommendation system,

image compression

try to group them

by similarity

produce the most

Homogeneous category

Examples: anti-spam filters, disease

detection, image recognition

“Cat”

When new data is provided,

AI recognizes patterns

of known categories

The model identifies

Data commonalities

in the same category

dog

the model is being trained

About classified data

by humans

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

3 types of machine learning algorithms

The model is trained based on

unique performance and

and the previous result

reinforcement learning

unsupervised learning



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