Using AutoML in Qlik Sense

[Troy_Raney]

This Techspert Talks session addresses:

• How to get started
• Making API calls
• Using Predictive Analysis

• 00:56 - What is AutoML?
• 01:31 - Iris demo intro
• 02:46 - Demo working AutoML Iris app
• 04:40 - How to setup data for AutoML
• 10:06 - ML Model Management
• 11:18 - How to add AutoML to a Sense App
• 13:56 - Prediction Analysis in a KPI object
• 15:19 - Batch predictions
• 16:35 - HR Promotion Analysis
• 18:00 - Additional Resources
• 19:00 - Q&A: Can the experiment data set be updated?
• 19:58 - Q&A: Is AutoML free?
• 20:36 - Q&A: What is the data size limit?
• 21:17 - Q&A: Can I choose my own index?
• 22:05 - Q&A: Is AutoML on for Qlik Cloud?
• 22:20 - Q&A: What data sources can be used?
• 22:52 - Q&A: Does AutoML work with Snowflake?
• 23:59 - Q&A: How to troubleshoot a connection error?
• 24:20 - Q&A: How do you schedule an the predictions?
• 24:43 - Q&A: Where can we find more documentation?

Q&A :

Q: I understand that I can invoke a production model through an API from Python. Are there any limitations to doing this? 

A:  We provide the APIs to invoke a model for real time predictions. These can be called from any platform/language like all Qlik’s APIs. In the case of python, the customer would call this using a library such as “requests”.  This functionality is only available for customers on a paid for tier.  More details can be found here.

Q: Is there a maximum amount of data sets which can be used for ML experiments? 

A: For each ML experiment, it uses one dataset.  There is no set limit on the number of datasets made available in Qlik Catalog, but there are limitations on the size of datasets.

Regarding dataset size, there are 2 limits in play:

1. The dataset size limit as set in the tier model.
      a. Included: 100K cells
      b. StartUp: 1M cells
      c. ScaleUp: 10M cells
      d. Premier: 100M cells

The data must be profiled by the catalog and this currently has a limit of 1GB file size. By using QVD or Parquet data files you can process more data.

Resources:

How To Get Started with Qlik AutoML

AutoML Hands On Tutorial

Qlik AutoML Demonstration Overview

Introduction to Qlik AutoML (Learning.Qlik.com)

Machine learning with Qlik AutoML (Help.Qlik.com)

Qlik AutoML on Qlik Cloud - sample data

Qlik Continuous Classroom AutoML courses

Click here to see video transcript

[KellyHobson]

**Video correction at 6:25** in regards to one-hot encoding.  In the video, AutoML used one-hot encoding to change categorical variables into a numeric representation.  I mention it would turn the 'Variety' (Virginica, Versicolor, Setosa) into numeric representation of 1,2,3 but it actually is creating a new binary column for each unique value in the categorical column.  The new column will be 1 if the original column value matches the value, and 0 otherwise.  1,2,3 suggest ordinal encoding  which is not occuring here and would not make sense because one flower variety is not greater or less than the other.

Reference: https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/AutoML/categorical-encod...