IntroductionSystem RequirementsPricing and PackagingSoftware updatesTypes of Models SupportedGetting Started with AutoMLData ConnectionsData Preparati...
This is a guide to get you started working with Qlik AutoML.
AutoML is an automated machine learning tool in a code free environment. Users can quickly generate models for classification and regression problems with business data.
Qlik AutoML is available to customers with the following subscription products:
Qlik Sense Enterprise SaaS
Qlik Sense Enterprise SaaS Add-On to Client-Managed
Qlik Sense Enterprise SaaS - Government (US) and Qlik Sense Business does not support Qlik AutoML
Pricing and Packaging
For subscription tier information, please reach out to your sales or account team to exact information on pricing. The metered pricing depends on how many models you would like to deploy, dataset size, API rate, number of concurrent task, and advanced features.
Qlik AutoML is a part of the Qlik Cloud SaaS ecosystem. Code changes for the software including upgrades, enhancements and bug fixes are handled internally and reflected in the service automatically.
Types of Models Supported
AutoML supports Classification and Regression problems.
Binary Classification: used for models with a Target of only two unique values. Example payment default, customer churn.
Customer Churn.csv (see downloads at top of the article)
another churn example
Multiclass Classification: used for models with a Target of more than two unique values. Example grading gold, platinum/silver, milk grade.
MilkGrade.csv (see downloads at top of the article)
Regression: used for models with a Target that is a number. Example how much will a customer purchase, predicting housing prices
AmesHousing.csv (see downloads at top of the article)
Getting Started with AutoML
What is AutoML (14 min)
Exploratory Data Analysis (11 min)
Model Scoring Basics (14 min)
Prediction Influencers (10 min)
Qlik AutoML Complete Walk Through with Qlik Sense (24 min)
Community Article for uploading data, training, deploying and predicting a model
Data for modeling can be uploaded from local source or via data connections available in Qlik Cloud.
You can add a dataset or data connection with the 'Add new' green button in Qlik Cloud.
There are a variety of data source connections available in Qlik Cloud.
Once data is loaded and available in Qlik Catalog then it can be selected to create ML experiments.
Data Preparation abilities
AutoML uses variety of data science pre-processing techniques such as Null Handling, Cardinality, Encoding, Feature Scaling. Additional reference here.
Using realtime-prediction API
Please reference these articles to get started using the realtime-prediction API
Example with Postman
Example with Python
Integration with Qlik Sense
By leveraging Qlik Cloud, predicted results can be surfaced in Qlik Sense to visualize and draw additional conclusions from the data.
How to join predicted output with original dataset
How to analyze SHAP values
If you need additional help please reach out to the Support group.
It is helpful if you have tenant id and subscription info which can be found with these steps.
Please check out our articles in the AutoML Knowledge Base.
Or post questions and comments to our AutoML Forum.
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.