CS231n: Convolutional Neural Networks Spring 2017
Stanford

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Lecture 1 _ Introduction to Convolutional Neural Networks for Visual Recognition-vT1JzLTH4G4.mp4152.68MB
Lecture 2 _ Image Classification-OoUX-nOEjG0.mp4134.76MB
Lecture 3 _ Loss Functions and Optimization-h7iBpEHGVNc.mp4169.43MB
Lecture 4 _ Introduction to Neural Networks-d14TUNcbn1k.mp4146.75MB
Lecture 5 _ Convolutional Neural Networks-bNb2fEVKeEo.mp4157.41MB
Lecture 6 _ Training Neural Networks I-wEoyxE0GP2M.mp4177.50MB
Lecture 7 _ Training Neural Networks II-_JB0AO7QxSA.mp4161.18MB
Lecture 8 _ Deep Learning Software-6SlgtELqOWc.mp4175.66MB
Lecture 9 _ CNN Architectures-DAOcjicFr1Y.mp4176.81MB
Lecture 10 _ Recurrent Neural Networks-6niqTuYFZLQ.mp4156.96MB
Lecture 11 _ Detection and Segmentation-nDPWywWRIRo.mp4171.19MB
Lecture 12 _ Visualizing and Understanding-6wcs6szJWMY.mp4187.59MB
Lecture 13 _ Generative Models-5WoItGTWV54.mp4169.06MB
Lecture 14 _ Deep Reinforcement Learning-lvoHnicueoE.mp4134.41MB
Lecture 15 _ Efficient Methods and Hardware for Deep Learning-eZdOkDtYMoo.mp4193.42MB
Lecture 16 _ Adversarial Examples and Adversarial Training-CIfsB_EYsVI.mp4160.34MB
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