- Sign up for an IBM Cloud account.
- Download or Clone this repo.
This tutorial takes about 20 minutes to complete if you already have an IBM cloud account set up.
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Create an instance of the Watson Machine Learning
- Go to the Watson Machine Learning page in the IBM Cloud Catalog.
- Click Create.
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Create an instance of the Cloud Object Storage
- Go to the Cloud Object Storage page in the IBM Cloud Catalog.
- Click Create.
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Create an instance of the IBM Cognos Dashboard Embedded
- Go to the IBM Cognos Dashboard Embedded page in the IBM Cloud Catalog.
- Click Create.
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Create an instance of the Watson Studio
- Go to the Watson Studio page in the IBM Cloud Catalog.
- Click Create.
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Click Get Started.
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Click Create a Project > Standard
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Name the project. Select Storage > cloud object storage. Create
- Upload the Dataset
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Open the dataset. Click on Refine to cleanse and shape it.
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Click on operation on the left - Select the Column "Item". Select Replace Substring and replace the strings with the following numbers as shown in the below gif.
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TShirt - 1, Formal Shirts - 2, Jeans - 3, Formal Trousers - 4, Blazers - 5, Jackets - 6, Shoes - 7, Heels - 8, Scarves - 9, Hats - 10
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- Select the right data type for every column by clicking on the 3 dots on the column > Convert column type > Select the right data type for the column.
- Save and Run the flow.
- Create an SPSS Modeler Flow. Upload the existing 'SPSS Flow - Store1Forecast.str' from the downloaded folder.
- Create another flow the same way and upload 'SPSS Flow - Store2Forecast.str'
- Run the flow
- Save the created models by clicking on the golden nugget for each model and saving it as a PMML script.
- Click on the saved model to deploy it as shown below. Repeat this for all the models.
- Launch RStudio
- Upload the folder Forecast to RStudio
- Update Watson Machine Learning credentials and model endpoints in the code and run the app!