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In the next few minutes, we'll talk about a subject called Deep Learning. There is no need for any theoretical background. To solve a problem using a deep learning solution, we start by describing our needs. We want to find a function that relates objects. We define a domain (starting point) and a counter domain (arrival point) We will do this by inserting the examples, one by one. Our input values go through basic mathematical operations (+, -, *, ÷) and then generate an output data, a result. The values with which our input data are operated throughout the process are called weights. With each example, we will calculate the loss, finding how much each one of these weights were responsible for the result of this rate of change.