hettlage (133) [Avatar] Offline
It is really great that you show in chapter 2 how things can go pear-shaped if you don't choose the correct step size / error normalisation.

But I wonder whether the approach taken in predict_shares.py really is the best one: Judging from the print output, the weight values do not seem to converge...

So maybe instead of normalising the error, you might consider normalising the article lengths and shares by dividing them by 1000, so that the values are in the interval [0, 1]. Then the weights converge rapidly (in less than 10,000 steps), and the resulting prediction model seems to be okay as well.
Nick Chase (27) [Avatar] Offline
That's a great suggestion. I'll definitely look into it on the final revision round.

---- Nick