https://yr-dev.tistory.com/entry/Lecture-1-Introduction-to-Convolution-Neural-Networks-for-Visual-Recognition [CS231n] Lecture1 필기본Lecture 1. Introduction to Convolution Neural Networks for Visual RecognitionCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.yr-dev.tistory.comhttps://yr-dev.tistory.com/entry/CS231n-Lecture2-%ED%95%84%EA%B8%B0%EB%B3%B8 [CS231n] Lec..

Lecture 16. Adversarial Examples and Adversarial TrainingCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.

Lecture 15. Efficient Methods and Hardware for Deep LearningCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.

Lecture 14. Deep Reinforcement LearningCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.

Lecture 13. Generative ModelsCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.

Lecture 12. Visualizing and UnderstandingCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.

Lecture 11. Detection and SegmentationCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.

Lecture 10. Recurrent Neural NetworksCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.

Lecture 9. CNN ArchitecturesCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.