Hi Michael,
I guess I am a bit late on the scene but I would really appreciate if you could share the sample code you used with me, too! I have greatly enjoyed your talk and thanks a lot for sharing that as well.
here is my e-mail address just in case : c.bakac@gmail.com
Cheers,
Cafer
Hi Michael,
Thank you for doing this video. I am new in MMM and have been searching a lot for good courses that relates to MMM with Bay Statistic. Unfortunately, I couldn’t find anything until your video. It is very helpful. I wonder do you mind sharing the code for this modeling exercise? And if you could stimulate the data, that would be the best! My email is gracecamc168@gmail.com.
Bests,
Grace
email: fmiraftab@berkeley.edu
Thank you!!!
Hello. great presentation. If this is still monitored, the sample code would be great to see. jeffrey.m.allard@gmail.com
Thanks!
People here might be interested in these resources:
And specifically, which has some code:
https://juanitorduz.github.io/pymc_mmm/
Hello,
Great presentation to understand more Bayesian approach to MMM. If there is a chance, could you share sample code with me ? Thanks in advance.
Thank you so much for the awesome youtube video. Would you mind sharing the code with me please? Thank you. email: anouk.barnoud@gmail.com
Thanks for this video! Could you send the sample code to emmag@ziprecruiter.com? Thanks so much!
Thank you very much for the great presentation ! I am new to Bayesian worlds and would love to learn more from your sample code. Could you please send it to my email : mikhail.krasner@pluto.tv
Thanks !
That was a great presentation! Could you also share the code with me please?
Best,
Prasanna
Very much enjoyed the presentation. Is the code available via the Git link?
To everyone who has asked for the code, it’s finally here: PyMC-Marketing: A Bayesian Approach to Marketing Data Science - PyMC Labs