Google Launches Beta Version of Cloud AI Platform Pipelines

A scalable machine learning workflow involves several steps and complex computations. These steps include data preparation and preprocessing, training and evaluating models, deploying these models and much more. While prototyping a machine learning model can be seen as a simple and easygoing task, it eventually becomes hard to track each and every process in an ad-hoc manner. To simplify the development of machine learning models, Google launches the beta version of Cloud AI Platform Pipelines, which will help to deploy robust, repeatable machine learning pipelines along with monitoring, auditing, version tracking, and reproducibility. It ensures to deliver an enterprise-ready, easy to install, a secure execution environment for the machine learning workflows. The AI platform in Google Cloud is a code-based data science development environment, which helps the machine learning developers, data scientists and data engineers to deploy ML models in a quick and cost-effective manner.