The theorical material can be found here.
Follow the instructions bellow:
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txtThe notebooks can be found here
| Date | Class | Topic |
|---|---|---|
| 20/09/2024 | 1 | Introduction |
| 27/09/2024 | 2 | SPAM Detector |
| 04/10/2024 | 3 | |
| 11/10/2024 | 4 | |
| 18/10/2024 | 5 | Anomaly Detection |
| 25/10/2024 | 6 | |
| 08/11/2024 | 7 | |
| 15/11/2024 | 8 | Mid-term Exam |
| 10/11/2024 | 9 | Malware Analysis |
| 17/11/2024 | 10 | |
| 24/11/2024 | 11 | |
| 01/12/2024 | 12 | Project |
| 08/12/2024 | 13 | |
| 15/12/2024 | 14 | |
| 22/12/2024 | 15 |
- S. Halder and S. Ozdemir, Hands-On Machine Learning for Cybersecurity: Safeguard your system by making your machines intelligent using the Python ecosystem. Packt Publishing Ltd, 2018.
- C. Chio and D. Freeman, Machine Learning and Security. O’Reilly, 2018.
- A. Parisi, Hands-On Artificial Intelligence for Cybersecurity: Implement smart AI systems for preventing cyber attacks and detecting threats and network anomalies. Packt Publishing Ltd, 2019.
- E. Tsukerman, Machine Learning for Cybersecurity Cookbook. Packt Publishing Ltd, 2019.
- J. P. Mueller and R. Stephens, Machine Learning Security Principles. Packt Publishing Ltd, 2019.
- Mário Antunes - mariolpantunes
This project is licensed under the MIT License - see the LICENSE file for details