lecture1_1647713580495.pdf
lecture10 - Recurrent Neural Networks_1647713582027.pdf
lecture11 - Detection and Segmentation_1647713582536.pdf
lecture12 - Visualizing and Understanding_1647713583609.pdf
lecture13 - Generative Models_1647713585400.pdf
lecture14 - Reinforcement Learning_1647713585736.pdf
lecture15 - Efficient Methods and Hardware for Deep Learning_1647713586164.pdf
lecture16 - Adversarial Examples and Adversarial Training_1647713586692.pdf
lecture2_1647713587149.pdf
lecture3 - Loss Functions_1647713592083.pdf
Backpropagation for a Linear Layer_1647713593207.pdf
Derivatives, Backpropagation, and Vectorization_1647713593587.pdf
lecture4 - Backpropagation and Neural Networks_1647713594404.pdf
lecun-98b_1647713595336.pdf
lecture5 - Convolutional Neural Networks_1647713598304.pdf
Gradient-Based-Training-of-Deep-Architectures_1647713600887.pdf
SGD-tricks-2012_1647713601260.pdf
efficient-backprop-lecun-98b_1647713601273.pdf
lecture6 - Training Neural Networks 1_1647713602562.pdf
lecture7 - Training Neural Networks 2_1647713604317.pdf
lecture8 - Deep Learning Software_1647713606119.pdf
GoogLeNet_1647713608936.pdf
ResNet_1647713609976.pdf
VGG-Net_1647713610242.pdf
imagenet-classification-with-deep-convolutional-neural-networks_1647713611999.pdf
lecture9 - CNN Architectures_1647713612906.pdf
figures_1647713633736.pptx
lecture1_1647713580495.pdf
lecture10 - Recurrent Neural Networks_1647713582027.pdf
lecture11 - Detection and Segmentation_1647713582536.pdf
lecture12 - Visualizing and Understanding_1647713583609.pdf
lecture13 - Generative Models_1647713585400.pdf
lecture14 - Reinforcement Learning_1647713585736.pdf
lecture15 - Efficient Methods and Hardware for Deep Learning_1647713586164.pdf
lecture16 - Adversarial Examples and Adversarial Training_1647713586692.pdf
lecture2_1647713587149.pdf
lecture3 - Loss Functions_1647713592083.pdf
Backpropagation for a Linear Layer_1647713593207.pdf
Derivatives, Backpropagation, and Vectorization_1647713593587.pdf
lecture4 - Backpropagation and Neural Networks_1647713594404.pdf
lecun-98b_1647713595336.pdf
lecture5 - Convolutional Neural Networks_1647713598304.pdf
Gradient-Based-Training-of-Deep-Architectures_1647713600887.pdf
efficient-backprop-lecun-98b_1647713601273.pdf
lecture6 - Training Neural Networks 1_1647713602562.pdf
lecture7 - Training Neural Networks 2_1647713604317.pdf
lecture8 - Deep Learning Software_1647713606119.pdf
GoogLeNet_1647713608936.pdf
imagenet-classification-with-deep-convolutional-neural-networks_1647713611999.pdf
lecture9 - CNN Architectures_1647713612906.pdf
figures_1647713628241.pptx
figures_1647713630519.pptx
figures_1649396348702.pptx
figures_1649396343711.pptx
figures_1649396338739.pptx
ResNet_1649396293938.pdf
VGG-Net_1649396294063.pdf
imagenet-classification-with-deep-convolutional-neural-networks_1649396294182.pdf
lecture9 - CNN Architectures_1649396294522.pdf
lecture8 - Deep Learning Software_1649396285886.pdf
GoogLeNet_1649396286056.pdf
Gradient-Based-Training-of-Deep-Architectures_1649396285010.pdf
SGD-tricks-2012_1649396285133.pdf
efficient-backprop-lecun-98b_1649396285222.pdf
lecture6 - Training Neural Networks 1_1649396285379.pdf
lecture7 - Training Neural Networks 2_1649396285634.pdf
lecture5 - Convolutional Neural Networks_1649396284689.pdf
lecture3 - Loss Functions_1649396276324.pdf
Backpropagation for a Linear Layer_1649396276534.pdf
Derivatives, Backpropagation, and Vectorization_1649396276672.pdf
lecture4 - Backpropagation and Neural Networks_1649396276755.pdf
lecun-98b_1649396276858.pdf
lecture16 - Adversarial Examples and Adversarial Training_1649396275353.pdf
lecture2_1649396275842.pdf
lecture15 - Efficient Methods and Hardware for Deep Learning_1649396263796.pdf
lecture12 - Visualizing and Understanding_1649396262750.pdf
lecture13 - Generative Models_1649396263371.pdf
lecture14 - Reinforcement Learning_1649396263545.pdf
lecture11 - Detection and Segmentation_1649396261845.pdf
lecture1_1649396250277.pdf
lecture10 - Recurrent Neural Networks_1649396257534.pdf