Cs231n spring2017 | ED8A16EBB346E14119A03371665306609E485F13

Cs231n spring2017

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Lecture 1 _ Introduction to Convolutional Neural Networks for Visual Recognition-vT1JzLTH4G4.mp4	152.7 MB
Lecture 10 _ Recurrent Neural Networks-6niqTuYFZLQ.mp4	157.0 MB
Lecture 11 _ Detection and Segmentation-nDPWywWRIRo.mp4	171.2 MB
Lecture 12 _ Visualizing and Understanding-6wcs6szJWMY.mp4	187.6 MB
Lecture 13 _ Generative Models-5WoItGTWV54.mp4	169.1 MB
Lecture 14 _ Deep Reinforcement Learning-lvoHnicueoE.mp4	134.4 MB
Lecture 15 _ Efficient Methods and Hardware for Deep Learning-eZdOkDtYMoo.mp4	193.4 MB
Lecture 16 _ Adversarial Examples and Adversarial Training-CIfsB_EYsVI.mp4	160.3 MB
Lecture 2 _ Image Classification-OoUX-nOEjG0.mp4	134.8 MB
Lecture 3 _ Loss Functions and Optimization-h7iBpEHGVNc.mp4	169.4 MB
Lecture 4 _ Introduction to Neural Networks-d14TUNcbn1k.mp4	146.8 MB
Lecture 5 _ Convolutional Neural Networks-bNb2fEVKeEo.mp4	157.4 MB
Lecture 6 _ Training Neural Networks I-wEoyxE0GP2M.mp4	177.5 MB
Lecture 7 _ Training Neural Networks II-_JB0AO7QxSA.mp4	161.2 MB
Lecture 8 _ Deep Learning Software-6SlgtELqOWc.mp4	175.7 MB
Lecture 9 _ CNN Architectures-DAOcjicFr1Y.mp4	176.8 MB
Total files 16