After
watching a video interview with Ericsson CTO, he mentioned that the machine
learning is data driven. I think, the following model is applicable for a
weather forecast. Operator would enter new data about an unknown weather
condition, so the computer learnt and it would be able to forecast correctly
next time if it happened again.
For
example, a weather condition is based on atmosphere pressure, cloud movement,
wind movement, temperature, etc. Thus system would have those data stored in
database for each case or weather condition. Based on collected data, system
could forecast rain, snow fall, etc.
This model could be used for other cases to
build an expert system with known data and facts, so the system could predict
those cases based on collected data. Operator would teach or enter new
(missing) facts and data, so the system could predict those in the future
correctly.
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