AI-Assisted Machine Learning Model Builder Interface
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Solution Overview
Problem
Conventional machine learning model building systems with drag-and-drop GUI interfaces lack assistance in building machine learning models, making it difficult for users without programming expertise to understand and execute the process.
Innovation Solution
A system and method that utilize an artificial intelligence platform and a machine learning model building host with an operation interface, non-transitory computer readable storage medium, and hardware processor to provide an interactive question-and-answer area, allowing users to input queries and receive answers through an API, thereby assisting in building machine learning models without programming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a drag-and-drop GUI interface is used to simplify machine learning model building operations, then ease of operation is improved, but the system lacks assistance in guiding users through the building process
Solution Approach 1:
The system implements an interactive question-and-answer area that provides real-time feedback and guidance to users during the machine learning model building process. The AI assistant monitors user actions and provides contextualized explanations, tips, and guidance information dynamically throughout the process, ensuring users receive appropriate assistance without disrupting the simplified drag-and-drop operation flow.
2Manufacturing precision
If conventional programming-based methods are used to build machine learning models, then manufacturing precision is improved, but time cost increases significantly
Solution Approach 1:
The system enables users to build machine learning models independently through the drag-and-drop interface with AI assistance, eliminating the need for professional programmers to perform time-consuming model building tasks. Users can directly configure and execute model building operations through the simplified interface while receiving contextualized guidance, significantly reducing the time cost while maintaining adequate model building precision for non-programmer users.
3Ease of operation
If a simplified drag-and-drop interface is provided, then ease of operation is improved, but users cannot understand how to build machine learning models
Solution Approach 1:
The AI assistant serves as an intermediary between the simplified drag-and-drop interface and the user, providing contextualized explanations and guidance information that bridges the gap between easy operation and process understanding. The assistant translates complex model building concepts into user-friendly explanations while maintaining the simplicity of the drag-and-drop interface, enabling users to both operate the system easily and understand the underlying processes.
Data Source
AI summary
A system of assisting in building machine learning model without programming and a method thereof is disclosed. A machine learning model building host provides an interactive question-and-answer area corresponding to a step process being executed, through an operation interface; the machine learning model building host provides a query message to an artificial intelligence platform through the Interactive question-and-answer area of an application programming interface, and the artificial intelligence platform provides the query message to a large language model to generate an answer message, the artificial intelligence platform transmits the answer message to the machine learning model building host, through the application programming interface, so as to achieve the technical effect of assisting in building a machine learning model without programming.