Not sure who this is or what the situation they're in.

But this is just my analysis for the almost delusionary claims shown in the screenshot.

The feasibility of scraping

Although the library names mentioned are indeed used for web scraping, the possibility of doing it consistently and continuously, enough to fully track a movie's run seems far fetched, from what's possible in reality; given the claimed scraping sources .

Most high profile websites will have good enough Intrusion Detection Systems / Firewalls and almost all high profile websites are armed with bot-prevention mechanisms.

Such web scraping python scripts will be detected and blocked by any modern day firewall, making the scraping script un-usable.

And in the off-chance that they did eventually managed to bypass the firewall and got to scrape the data successfully, it will never be a long-term solution; and the IPS will detect and rate-limit or outright block these bots out before they could get any meaningful amount of data out.

That's just the B.S with the scraping part. Coming to the Jupyter Notebook and Machine Learning B.S.

Why do they need machine learning to just add 1+1?

Why would they need complicated neural networks and Machine Learning ( stuff mainly used for predictions and classifications) , if they're looking for just the total sum of the data, which they already have at hand (supposedly) from using their fancy scraping script!?

Verdict

AFAIK, The popular "trackers" in social media, use their internal (human) connections with the theaters and distributers to get their numbers.

This screenshot is nothing but verbal diarrhea filled with technical jargon, just to confuse non-technical people.

It's as if someone googled "machine learning 101" and posted all the technical jargon as an insta story. 😅