Systems that rely on Deep Learning, however

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sumonasumonakha.t
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Systems that rely on Deep Learning, however

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Deep Learning uses more sophisticated tools, making the results more accurate. Going back to the Amazon example, the technology identifies exceptions so as not to make unqualified suggestions. Imagine this: if out of 1000 customers searching for “smart TVs“, 800 continue their search with “home theater“, the software understands this is a relevant recommendation. With Machine Learning, if five users start a search for “shoes” after searching for “smartTV“, the system could assume it is a valid recommendation.


Know that these are unrelated products, preventing exceptions from becoming rules when it comes tunisia telegram number list to user behavior. Deep Learning uses more complex networks to conclude that this example is not a causal search. Although there is an occurrence, it is not a relevant result for the user. In this sense, Deep Learning is able to understand human thoughts in more detail than Machine Learning.


Natural Language Processing (NLP) The last pillar of AI is Natural Language Processing (NLP). This is responsible for polishing results, making them more natural and human-like. For example, several e-commerce businesses currently use chatbots for customer service. However, the quality of this technology lies in the presence of NLP. When it is not incorporated into the solution, the bot becomes artificial. It is unable to improve its language to make it more similar to the one used by customers.
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