This research proposes an automatic selection method for Artificial Intelligence a cloud computer environment. By leveraging the capabilities of cloud computing platforms, users can effortlessly and intelligently constructArtificial Intelligence models tailored to address real-world problems. The proposed method eliminates the need for users to manually set up the Artificial Intelligence operating environment, select learning algorithms, or fine-tune complex Artificial Intelligence functions and parameters. Instead, users can simply utilize a web-based interface to upload sample data, enabling the seamless integration of Artificial Intelligence within the cloud computing paradigm. This approach liberates Artificial Intelligence from environmental constraints and harnesses the inherent advantages of cloud computing, thereby enhancing user transparency and significantly reducing the entry barrier to Artificial Intelligence. The automatic selection method presented here addresses the limitations associated with unpredictable model building selection, manual parameter adjustment based on experience, and the challenges faced by non-expert users when applying Artificial Intelligence in real-life scenarios.

Automatic selection, Artificial Intelligence, cloud computing, model building, parameter adjustment, user transparency, entry barrier reduction.