- Preventing adversarial examples? https://medium.com/@ageitgey/machine-learning-is-fun-part-8-how-to-intentionally-trick-neural-networks-b55da32b7196 18 comments learnmachinelearning
- How to Intentionally Trick Neural Networks: A Look into the Future of Hacking https://medium.com/@ageitgey/machine-learning-is-fun-part-8-how-to-intentionally-trick-neural-networks-b55da32b7196 48 comments programming
Linking pages
- GitHub - ZuzooVn/machine-learning-for-software-engineers: A complete daily plan for studying to become a machine learning engineer. https://github.com/ZuzooVn/machine-learning-for-software-engineers/blob/master/README.md 111 comments
- GitHub - ZuzooVn/machine-learning-for-software-engineers at producthunt https://github.com/ZuzooVn/machine-learning-for-software-engineers?ref=producthunt 0 comments
Linked pages
- Download Python | Python.org https://www.python.org/downloads/ 65 comments
- Keras: the Python deep learning API https://keras.io 46 comments
- [1602.02697] Practical Black-Box Attacks against Machine Learning http://arxiv.org/abs/1602.02697 32 comments
- CUDA Toolkit 12.1 Downloads | NVIDIA Developer https://developer.nvidia.com/cuda-downloads 5 comments
- Keras.js - Run Keras models in the browser https://transcranial.github.io/keras-js/#/ 3 comments
- Keras Applications https://keras.io/applications/ 3 comments
- [1412.6572] Explaining and Harnessing Adversarial Examples http://arxiv.org/abs/1412.6572 1 comment
- [1607.02533] Adversarial examples in the physical world http://arxiv.org/abs/1607.02533 0 comments
- [1312.6199] Intriguing properties of neural networks http://arxiv.org/abs/1312.6199 0 comments
- NIPS 2017: Non-targeted Adversarial Attack | Kaggle https://www.kaggle.com/c/nips-2017-non-targeted-adversarial-attack 0 comments
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