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AI for Digital Forensics Hands-on Labs
Overview
Welcome to the AI for Digital Forensics Hands-on Labs repository! This repository provides a series of hands-on labs designed for students and faculty to explore the importance and application of AI in digital forensics. Through interactive exercises, you will learn how to train and test AI models, work with datasets, and apply AI techniques to real-world forensic scenarios.
Key Features
- Hands-on Labs: Step-by-step guides to implement AI techniques in digital forensics.
- Pre-collected Datasets: Curated online datasets for training and testing AI models.
- Model Training & Testing: Learn how to train, evaluate, and optimize AI models.
- Custom Data Support: Apply AI models to your own forensic datasets.
- Google Colab Support: Run all labs in the cloud with Google Colab—no local setup required.
- Open-source Code: All source code is open and modifiable based on student and faculty needs.
Getting Started
Prerequisites
To complete these labs, you will need:
- A Google account (for Google Colab)
- Basic knowledge of Python and machine learning concepts
- Familiarity with digital forensics fundamentals (recommended)
Running the Labs
Add the following string before each each Jupyter files (incluidng path)
https://colab.research.google.com/github/frankwxu/AI4DigitalForensics/blob/main/
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Lab 1: Hate speed detection
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Lab 2: Gun detection
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Lab 10: Reinforcement Learning
Contributing
We welcome contributions from students, faculty, and researchers! Feel free to:
- Improve existing labs
- Add new datasets or models
- Report issues or suggest enhancements
License
This project is open-source and available under the MIT License.
Contact
For any questions, feel free to open an issue or reach out to us at fxu at ubal dot edu. Happy learning! 🚀