Prophet

Rodrigo Agundez looks at Prophet, Facebook’s new API for store sales forecasting:

The data is of a current client, therefore I won’t be disclosing any details of it.

Our models make forecasts for different shops of this company. In particular I took 2 shops, one which contains the easiest transactions to predict from all shops, and another with a somewhat more complicated history.

The data consists of real transactions since 2014. Data is daily with the target being the number of transactions executed during a day. There are missing dates in the data when the shop closed, for example New Year’s day and Christmas.

The holidays provided to the API are the same I use in our model. They contain from school vacations or large periods, to single holidays like Christmas Eve. In total, the data contains 46 different holidays.

It looks like Prophet has some limitations but can already make some nice predictions.

Related Posts

Kafka And The Differing Aims Of Data Professionals

Kai Waehner argues that there is an impedence mismatch between data engineers, data scientists, and ML production engineers: Data scientists love Python, period. Therefore, the majority of machine learning/deep learning frameworks focus on Python APIs. Both the stablest and most cutting edge APIs, as well as the majority of examples and tutorials use Python APIs. […]

Read More

Solving The Monty Hall Problem With R

Miroslav Rajter builds a Monty Hall problem simulator using R: The original and most simple scenario of the Monty Hall problem is this: You are in a prize contest and in front of you there are three doors (A, B and C). Behind one of the doors is a prize (Car), while behind others is […]

Read More

Categories

March 2017
MTWTFSS
« Feb Apr »
 12345
6789101112
13141516171819
20212223242526
2728293031