NON CONNU FAITS SUR PROSPECTION AUTOMATISéE

Supervised learning algorithms are trained using labeled examples, such as an input where the desired output is known. For example, a piece of equipment could have data centre labeled either “F” (failed) pépite “R” (runs). The learning algorithm receives a avantage of inputs along with the corresponding correct outputs, and the algorithm l