Hello, Data Explorers! 🚀 In this video, we show you how access a deployed AutoML model straight from a Python code. You will learned about AutoML deployment, Real-Time API, API Keys, and how to implement this solution in Python. We will also mention a couple of use case scenarios for a solution like this. 👍 If you appreciate this video, like it and share it. 🔍 Follow us: Youtube: https://youtube.com/@datavoyagers Linkedin: https://www.linkedin.com/company/datavoyagers

Hello, Data Explorers! 🚀 In this video, we show you how to use AutoML Real-Time API to run predictions dynamically from a Qlik application UI without the need to reload the data or run a prediction job. It allows you to include What-If scenarios in a very robust and straight forward way. 👍 If you appreciate this video, like it and share it. 🔍 Follow us: Youtube: https://youtube.com/@datavoyagers Linkedin: https://www.linkedin.com/company/datavoyagers Code used in the video

Author: Igor Alcantara Qlik Answers is a powerful tool within the Qlik Cloud platform, designed to harness the capabilities of AI by providing contextually relevant answers from unstructured data. Many great people are already providing incredible use cases for this tool. The way I decided I could contribute more was to run a few exercises and analyses, like the article I published on this blog about my first impressions of Qlik Answers and the many other posts I shared on m