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This article provides step by step guidelines for uploading a dataset (csv from local machine), creating a model, deploying a model, and generating predictions with Qlik AutoML on Qlik Cloud environment.
Steps
- Log into Qlik Cloud
- Click +Add new and select "Dataset"
- Select "Upload data file", select Browse, navigate to your file, then click 'Upload'
- Once uploaded, click +Add New -> 'New ML Experiment'
- Give ML experiment a meaningful name and assign to a space, then click 'Create'
- Select the dataset you uploaded
- Select the target variable and features to include in the model. On the right hand side you have additional options to select which algorithms, hyperparamteter optimization, and data prep steps. We are sticking with the defaults. Click 'Run Experiment' on the bottom right side of screen.
- Model metrics and insights are displayed on the page. If you would like to refine the model, you can select 'Configure V2' on the bottom right. If you are ready to deploy model, then click 'Deploy.'
- Give the model a meaningful name and then click 'Deploy'
- At the top of the page you will get a notification, click this to open the deployed model. If you 'miss' the notification, you can always navigate to Home -> Catalog -> and search for type 'ML Deployments'. Once opened, you will see a page with metadata about the deployed model. At the bottom right, you will see an option to 'Create Prediction'
- Select an apply dataset. In this example, I am using the same dataset I used to train the model. (Not advisable but easy for learning purposes).
- Name your prediction dataset something meaningful and add to working space. Click 'Confirm'
For this particular example, we have an ID column and I will use this as the index column (and later for joining) - Congratulations! You now have a generated predictions on using your deployed model.
If you navigate to 'Home' - > 'Catalog' -> 'Data' you will see your predicted outputs.
Related Content:
Qlik AutoML: Overview of SHAP values
Environment
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
Hi! Inspired by yesterdays blog post I had a go at this, but the "New ML experiment" item under "+ Add new" is not there. I have enabled "Machine learning endpoints", but have the impression that that is for enabling Sense to get the ML++ connections available.
Any docs or tips?
Best regards
Jan
@KellyHobson I tried three times, got an error on step # 13 above. Error message: "id is a model feature and is not a valid index column", am I missing a step? On step # 12 above, id was set to index column?
