This article explores how to use Pipcook 2.0 to train, deploy, and publish a model.
This article uses Pipcook to train a form recognition model and uses this model to improve the efficiency of form development.
This article discusses our ideas about AI in the frontend field and efforts to implement code intelligent generation.
This article explains the similarities and differences between Low-Code and No-Code development and their benefits.
This article is a part of the article series discussing how to generate frontend code from design files intelligently.
This article guides you through the implementation of your own frontend intelligent project and use of machine learning to address programming problems.
This article introduces Pipcook and discusses how it can be optimized and used for an intelligent frontend.
This article describes how Pipcook is integrated with TensorFlow and how the underlying models of tfjs-node are used to build a machine learning pipeline.
This article discusses upgrading programming through machine learning and intelligent thinking.
