DDE-1/Regression.md

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-## Regression in ML
+## Regression Problem
+
+In regression tasks, we use the data to predict,the correct real-valued labels of the instances  as closely as possible. Our objective is to estimate real numbers, so it is not reasonable to expect that any model can predict precisely the correct values. Therefore, we are interested in predictions that are "good enough". Herein, the measure of error is formulated as a function of the difference(s) between the real-valued label(s) predicted and the true values in the training set. 
+
+The simplest algorithm for regression known as linear regression. Here the proposed solution assumes that the label can be generated as a linear combination of the input variables:
+
+```math 
+y(x, w) = w0 + w_1*x_1 + . . . + w_i*x_i
+```
 
 ## Additional Sources