It doesn’t take a 50 engineers team and a 1M lines of code project to predict anything these days.
new_pred = regressor.predict(new_dataset)Just one line of code. As simple as that. The real work (for which you need brain power more than lines of code) is in: 1) Selecting the variables that truly matter to predict a new variable 2) Compose and clean up the training data set (and keep it updated!) 3) Try different prediction models, score them and use the most efficient 4) Provide a dataset with known values to predict unknown values 5) Format the outputs in a way that makes business sense For a simple supervised learning / linear regression prediction of reach within Facebook, for a given budget and a given age group, you can check out my -short- example here: https://github.com/leocelis/predictions/blob/master/predict_reach.py
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