Show Notes
In this episode Tania and I chat through how we learnt about AI security and adversarial machine learning, and how you can too!
Some resources we mention: - Crash Course AI https://thecrashcourse.com/topic/ai/ - 3 Blue 1 Brown https://www.youtube.com/c/3blue1brown - Kaggle https://www.kaggle.com/learn/intro-to-machine-learning - Hands-on ML textbook (more for 'classic' machine learning - still really important to understand 'modern' models) https://www.booktopia.com.au/hands-on-machine-learning-with-scikit-learn-keras-and-tensorflow-3e-aurelien-geron/book/9781098125974.html?gad_source=1&gclid=CjwKCAiA9dGqBhAqEiwAmRpTC3W7SbJJOrI8fEi-19OxvyNLElA8Nk7iKH6nE4KDm1iLlySKgb114hoCcG8QAvD_BwE - The paper that started it all (or at least a lot of it) https://arxiv.org/abs/1312.6199 - Adversarial Robustness Toolbox https://adversarial-robustness-toolbox.org/ - Cleverhans https://cleverhans-lab.github.io/ - Darknet diaries (please someone introduce me to Jack) https://darknetdiaries.com/ - Rob Miles https://www.youtube.com/@RobertMilesAI - Import AI https://jack-clark.net/ - AI Daily Brief https://www.youtube.com/channel/UCKelCK4ZaO6HeEI1KQjqzWA - Less Wrong https://www.lesswrong.com/ - Unsupervised learning https://danielmiessler.com/ - OWASP ML Top 10: https://owasp.org/www-project-machine-learning-security-top-10/ - ML Safety https://course.mlsafety.org/about - Anatomy of an AI system: https://anatomyof.ai/
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