Tutorial of AI Kit with Raspberry Pi From Zero to Hero

Play your AI Kit from Beginner to Expert
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🛠️ About The Project

This course is designed to teach you how to harness the power of AI on the Raspberry Pi, with a particular focus on using an AI kit to perform essential computer vision tasks. Throughout the course, you'll learn how to integrate AI into real-world IoT (Internet of Things) applications, from object detection and image classification to more complex visual recognition tasks. We will guide you step-by-step through setting up your Raspberry Pi, using AI frameworks, and deploying these models in various practical scenarios. Whether you are a hobbyist, a student, or a professional, this course will provide you with the foundational knowledge and hands-on experience necessary to bring AI-driven solutions to life on resource-constrained devices like the Raspberry Pi.

📚 Pre-requisites

Raspberry Pi AI Kit	reComputer R1000	Raspberry Pi 5
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📚 Recommended Reading

Machine Learning

Introduction to Machine Learning with Python

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Computer Vision

Programming Computer Vision with Python

Deep Learning for Computer Vision

Large Language Model

Deep Learning for Natural Language Processing: Creating Neural Networks with Python

🧱 Built With

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🗺️ Roadmap

⏳ Indicates in progress, ✔️ indicates completed.

Chapter 1 [In Progress, Excepted Completion: November 2024]

• ✔️ Introduction of Artificial Intelligence
• ✔️ Introduction of Deep Neural Network
• ✔️ Introduction of Convolutional Neural Network
• ✔️ Introduction of Computer Vision
• ✔️ Introduction of Large Language Model

Chapter 2 [In Progress, Excepted Completion: December 2024]

• ✔️ Introduction to Pytorch in Raspberry Pi Environment
• ✔️ Introduction to TensorFlow in Raspberry Pi Environment
• ✔️ Introduction to OpenCV in Raspberry Pi Environment
• ✔️ Introduction to Ultralytics in Raspberry Pi Environment
• ⏳ Introduction to Hailo in Raspberry Pi Environment

Chapter 3 [In Progress, Excepted Completion: January 2025]

Chapter 4 [Completed: November 2024]

• ✔️ Setup Ollama on RaspberryPi
• ✔️ Run Llama on RaspberryPi
• ✔️ Run Gemma2 on RaspberryPi
• ✔️ Run Phi3.5 on RaspberryPi
• ✔️ Run Multimodal on RaspberryPi
• ✔️ Use Ollama with Python

Chapter 5 [In Progress, Excepted Completion: December 2024]

• ✔️ Training
• ✔️ Converting
• ✔️ Deploying

Chapter 6

Open for everyone to contribute

See the open issues for a full list of proposed features (and known issues).

🤝 Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please follow this Contributor Guidelines and contribute your own code.

Don't forget to give the project a star! Thanks again!

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📄 License

Distributed under the MIT License. See LICENSE for more information.

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