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AI Playgrounds, a repository created to explore, experiment, and prototype Proof of Concepts (POCs) around AI tools and technologies using Python.

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AI Playgrounds

Python Streamlit Selenium

Welcome to AI Playgrounds, a repository created to explore, experiment, and prototype Proof of Concepts (POCs) around AI tools and technologies using Python. This repository serves as a dynamic space for quick experimentation and learning in the ever-evolving field of Artificial Intelligence.

Objectives

  • Experimentation: Test and build quick POCs around AI tools, frameworks, and techniques.
  • Learning: Provide a space for learning, experimenting, and iterating on AI concepts.
  • Expansion: Continuously expand with new POCs, keeping the repository fresh and relevant.

Repository Structure

1. AI Case Studies

  • Focuses on applying AI techniques to solve real-world problems.
  • Includes projects like Hotel Booking Cancellation Prediction and Optical Character Recognition (OCR).
  • Read more

2. AI Engineering Studio

  • Focuses on building AI agents and tools for advanced engineering use cases.
  • Includes projects like MCP Agent and Multi-Tool Agent.
  • Read more

Contributions

Contributions are warmly welcomed! Whether it's improving existing POCs, adding new experiments, or sharing ideas, your inputs are highly valued. Feel free to open issues or submit pull requests to collaborate.

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AI Playgrounds, a repository created to explore, experiment, and prototype Proof of Concepts (POCs) around AI tools and technologies using Python.

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