Forecasting Demand, Finding Sales Data - Facebook Prophet, Google Trends & Python
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- Опубліковано 6 жов 2024
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Let's talk about forecasting demand, this is as old as money and commerce. Rainy season, you stock up on umbrellas; winter, winter coats, etc. I'll walk you through a simple example using open-source FBProphet in Python, one of the most powerful forecasting engines and also one of the easiest to use (once you manage to install it).
For source code:
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Stackline demand stats:
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You're a really good teacher. Even though I mainly use R as a marketing student, your videos offer creative and interesting insights.
Most of these ideas can be translated into R and FBProphet has an R version as well. Thanks for the kind words!
Great explanation! The best I saw
Great video! Thanks Manuel!
Thanks, Anne-Marie!
Thanks 👍 It was useful and interesting video !
This was a great video. It was very helpful. Thanks!
Amazing video. Thank you.
Thanks, Marco!
How do you use prophet model for where their is promotional price periods involved in the historical data? For instance, what if there was a frequent promotion on a consumer product that inflated demand, i.e. a box of cereal is normally $3.99, but then goes on sale for 2 weeks for a price point of $2.50. And this happens 13 times a year? That is what I am trying to solve for...
Hey! I'm facing a similiar problem. You don't want the model to learn from that history or behaviour, becasue it's been kind of manipulated. How did you solve it?
This was really nice. I have a quick question: is it possible to use prophet when I just have "year" in my dataset? Many thanks in advance.
Not ideal - as it won't capture yearly cycles but if there's monthly or weekly cycles, that'll work.
@@viralml many thanks!
Hi Manuel! Great video! What is the best way to measure accuracy? For example, get the MAE with -12 months? Thanks!
Is there a way to include google trends and combine it with own past sales data?
Very interesting thank you sir