2025. 5. 2. 16:18ㆍArtificial Intelligence/CS231n (Stanford)
[CS231n] Lecture1 필기본
Lecture 1. Introduction to Convolution Neural Networks for Visual RecognitionCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture2-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture2 필기본
Lecture 2. Image classificationCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture3-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture3 필기본
Lecture 3. Loss Functions and OptimizationCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture4-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture4 필기본
Lecture 4. Introduction to Neural NetworksCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture5-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture5 필기본
Lecture 5. Convolutional Neural NetworkCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture6-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture6 필기본
Lecture 6. Training Neural Networks ICS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture7-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture7 필기본
Lecture 7. Training Neural Networks IICS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture8-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture8 필기본
Lecture 8. Deep Learning SoftwareCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture9-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture9 필기본
Lecture 9. CNN ArchitecturesCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture10-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture10 필기본
Lecture 10. Recurrent Neural NetworksCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture11-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture11 필기본
Lecture 11. Detection and SegmentationCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture12-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture12 필기본
Lecture 12. Visualizing and UnderstandingCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture13-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture13 필기본
Lecture 13. Generative ModelsCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture14-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture14 필기본
Lecture 14. Deep Reinforcement LearningCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture15-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture15 필기본
Lecture 15. Efficient Methods and Hardware for Deep LearningCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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https://yr-dev.tistory.com/entry/CS231n-Lecture16-%ED%95%84%EA%B8%B0%EB%B3%B8
[CS231n] Lecture16 필기본
Lecture 16. Adversarial Examples and Adversarial TrainingCS231n: Deep Learning for Computer Vision (Stanford University) 강의를 바탕으로 정리한 자료입니다.
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