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Mar 19 '221 0
Mar 19 '22GarryMachine learning methods do the same thing - they look for hidden dependencies between data. The largest class of problems that are solved by these methods are various forecasts. Check out more here - https://artechyapi.com/why-consider-functional-programming/ A clear example is a forecast of traffic jams. The level of traffic congestion is influenced by many factors: the location of the road, the season, the day of the week, the time of day, the weather, the number of accidents on the site, and so on. All this data affects the final result, but a person cannot calculate this influence, because there is a huge amount of data. And a machine learning model can easily do this and produce a traffic forecast for a specific section of the road at a specific time.Machine learning methods do the same thing - they look for hidden dependencies between data. The largest class of problems that are solved by these methods are various forecasts. Check out more here -...See moreYou need to sign in to comment
