it seems like the first four weeks are not that far offalthough we clearly see that there is something wrong with our initial assumption that the underlying model is straight line plushow good or bad actually is the error of , , the absolute value of the error is seldom of use in isolation howeverwhen comparing two competing modelswe can use their errors to judge which one of them is better although our first model clearly is not the one we would useit serves very important purpose in the workflowwe will use it as our baseline until we find better one whatever model we will come up with in the futurewe will compare it against the current baseline towards some advanced stuff let us now fit more complex modela polynomial of degree to see whether it better "understandsour dataf sp polyfit(xy print( parray( - - + sp poly ( pprint(error( xy) + ]the following chart shows the model we trained before (straight line of one degreewith our newly trainedmore complex model with two degrees (dashed)