'How to train multi item timeseries forecasting in Sagemaker?
I have data like below.
date sku unitprice trand_item target
2018-01-01 A 10 Black 3
2018-01-02 A 10 Black 7
2018-01-03 A 10 Black 0
2018-01-04 A 10 Black 13
.
.
.
2017-08-01 B 20 White 4
2017-08-02 B 20 White 0
2017-08-03 B 20 White 17
2017-08-04 B 20 White 9
.
.
.
Every timestamp is filled in 'D' without blank and 'sku' is item number. I have 25 items and i want to forecast 'target'. Also want to use 'unit price', 'trand_item' for meta data.
How can i train timeseries forecasting model in sagemaker? 1 model for 25 items. (For example, i want to forecast 30days for each item's 'target'.)
Please help me...
Solution 1:[1]
If you have at least 300 rows you can use DeepAR. It supports grouping, such as by SKU
Otherwise, you'd want to bring your own algorithm, such as sktime
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | Neil McGuigan |