Machine learning with Qlik Predict
Automated machine learning finds patterns in your data and uses them to make predictions on future data. Machine learning experiments in Qlik Cloud Analytics let you collaborate with other users and integrate your predictive analytics in Qlik Sense apps. In addition to making predictions, you can do an in-depth analysis of the key features that influence the predicted outcome.
Load historical data from the catalog, start the automated machine learning process, and then choose the best-fitting machine learning model for your use case. Deploy the models to make predictions on the outcome of business problems. Explore the variables that impact the predicted outcome, and gain a thorough understanding of your data.
Alternatively, developers can integrate Qlik Predict capabilities into their own workflows using the Machine Learning API. For a tutorial to help you get started, see Automated machine learning tutorial.
Qlik Cloud Government does not support Qlik Predict.
Machine learning fundamentals
Before you create an experiment, you need to define a machine learning question and prepare a dataset. Learn more here.
Creating experiments
Get an overview of the automated machine learning process and start creating experiments.
Interpreting model performance
Learn about the model metrics that are available for scoring predictive models.
Refining models
How can you improve your predictive model? Learn more here.
Working with ML deployments
Learn about deploying models, making predictions, using the API, and more.
Tutorial – Generating and visualizing prediction data
This tutorial shows you how to create and train an experiment, deploy a model and generate predictions, and visualize the prediction data in a Qlik Sense app.