Azubi-Africa/Career_Accelerator_LP3-Regression
Record type:
project
Creator:
Azu
Host:
Live Project 2 for the Post Business Analytics Programme (BAP) Career Acceleration Programme
# **Time Series Regression Analysis (Corporation Favorita)**
**Scenario**: You are a data scientist in Corporation Favorita, a large Ecuadorian-based grocery retailer. Corporation Favorita wants to ensure that they always have the right quantity of products in stock. To do this you have decided to build a series of machine learning models to forecast the demand of products in various locations. The marketing and sales team have provided you with some data to aid this endeavor. Your team uses CRISP-DM Framework for Data Science projects
This is a **time series regression analysis** problem. In this project, you'll
predict store sales on data from Corporation Favorita, a large
Ecuadorian-based grocery retailer.
Specifically, you are to **build a model** that more accurately predicts
the unit sales for thousands of items sold at different Favorita stores.
The training data includes dates, store, and product information,
whether that item was being promoted, as well as the sales numbers.
Additional files include supplementary information that may be useful in
building your models
**File Descriptions and Data Field Information**
**train.csv**
- The training data, comprising time series of features store_nbr, family,
and onpromotion as well as the target sales.
- **store_nbr** identifies the store at which the products are sold.
- **family** identifies the type of product sold.
- **sales** gives the total sales for a product family at a particular store
at a given date. Fractional values are possible since products can be sold in
fractional units (1.5 kg of cheese, for instance, as opposed to 1 bag of chips).
- **onpromotion** gives the total number of items in a product family that
were being promoted at a store at a given date.
**test.csv**
- The test data, having the same features as the training data. You will predict the target sales for the dates in this file.
- The dates in the test data are for the 15 days after the last date in the tr …