It is no different in the field of manufacturing products, the prices of products change continuously and quickly, affecting the sellers of products and consumers in one way or another.
Thus, the need for price forecasting appeared. We, as data scientists, decided to build a model to predict product prices in Jordan, based on many factors affecting the price.
A simple glimpse of our data, the food price Jordan dataset includes the price of 35 commodities that gather into 8 categories from 2011 to 2022, from 2011 to 2016 the commodity price represents the national average price in Jordan, and from 2017 to 2022 the data include the price in each governorate in Jordan.
The conclusion: The price of each commodity is affected differently, but in general we can see that our features correlate with the price. and to know more about the datasets and features extraction check this presentation Price forecast.
Using these features we will build our model to predict the price of food products in Jordan, to know more about the model check this presentation Price Forecast Model.
- part 1
- contains data analysis
- part 2
- contains model building