机器学习项目 - 后人工智能与数据分析 - 瓦格纳·佩雷拉

This project explores the application of different artificial intelligence (AI) approaches for image recognition tasks. The methodology involved utilizing two distinct AI tools: Teachable Machine, which learns from provided examples, and Google AI Studio, an AI platform that responds to text-based commands. The primary objective was to create an image recognition process using these diverse AI paradigms. Specific objects, namely STEVE and TUX, were chosen as learning targets for the AI models. As an additional component, a simulation of Teachable Machine's functionality was developed within AI Studio. This comparative exercise aimed to highlight the differences between the two AI methods and facilitate deeper learning. The practical implementation demonstrates the capabilities of AI in visual pattern recognition and provides insights into how different AI learning mechanisms operate. This hands-on experience is crucial for understanding the nuances of AI development and its potential applications in post-AI and data analysis fields.