PROFESJA -=BarManI=- KRAKÓW

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In the marketing field, artificial intelligence will tell us very quickly if more coats or more shoes are being sold on our eCommerce, because we have first taught it what clothing items are, which ones and how many there are, the colors, etc. Third level: deep learning Deep learning occurs when the data entered into the artificial intelligence system is in enormous quantities (big data) and consequently the algorithms learn from their errors, creating new ones and updating themselves. More specifically, we are in the case where it is no longer enough to differentiate dogs from cats, but there is a need to learn the different breeds , thus creating levels of information that go deeper.

In this case we ask the machine questions (input) and give it a series of answers (neural networks, the outputs). The answers are the algorithms (i.e. the functions to be performed) to the questions, which asked many times will allow the machine to learn and generate new algorithms seo expater bangladesh ltd from the errors of the previous ones. When new information is presented to the machine, the algorithms evolve and learn even better and faster. But how did we manage to use artificial intelligence without the need to program algorithms and ask “Hey Google, turn on the radiators when the internal temperature drops below Download-ebook-marketing-artificial-intelligence Return to index.



NLP Natural Language Processing and NLG Natural Language Generation Your customers are conditioned to communicate with Alexa, Siri or other “voice search” systems as a tool, without necessarily understanding that these machines filter voice using an artificial intelligence application called Natural Language Processing (NLP). Part of NLP is the ability to understand language, detect tone, and understand the complexity of a question. If you ask Siri a question, it first has to understand what you're asking in common language, or jargon. Once he understands and only then can he search for the answer online, translate.
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[warpd]

Amad

[warpd]

Wind

[warpd]

Jenn

[warpd]

Mult

[warpd]

Mult

[warpd]

Mult

[warpd]

mail

[warpd]

Fran

[warpd]

Barr

[warpd]

Stra

[warpd]

Geor

[warpd]

Fort

[warpd]

ANSW

[warpd]

iPod

[warpd]

Unde

[warpd]

Alex

[warpd]

pass

[warpd]

tuchkas

[Reklama]