Create a machine learning model pipeline to choose the best model for your problem

It was inevitable to expect artificial intelligence, which facilitates every aspect of our lives, to facilitate its own development process. Building better models requires more complex time-intensive and costly AI procedures, which require expertise from cleansing the data to feature engineering, designing the architectures to parameter optimization. To ease this process and make it efficient in terms of time and effort, you need to automate these workloads. With the aim of creating AI for AI, IBM introduced a service on Watson Studio called AutoAI. AutoAI can be run in public clouds and in private clouds, including IBM Cloud Pak for Data.