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neuralnets-2012-001

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File Name
Size
01_Lecture1/01_Why_do_we_need_machine_learning_13_min.mp4
15 MB
01_Lecture1/01_Why_do_we_need_machine_learning_13_min.pdf
3.9 MB
01_Lecture1/01_Why_do_we_need_machine_learning_13_min.pptx
3.6 MB
01_Lecture1/01_Why_do_we_need_machine_learning_13_min.srt
18 kB
01_Lecture1/01_Why_do_we_need_machine_learning_13_min.txt
12 kB
01_Lecture1/02_What_are_neural_networks_8_min.mp4
9.8 MB
01_Lecture1/02_What_are_neural_networks_8_min.srt
12 kB
01_Lecture1/02_What_are_neural_networks_8_min.txt
7.5 kB
01_Lecture1/03_Some_simple_models_of_neurons_8_min.mp4
9.3 MB
01_Lecture1/03_Some_simple_models_of_neurons_8_min.srt
11 kB
01_Lecture1/03_Some_simple_models_of_neurons_8_min.txt
6.9 kB
01_Lecture1/04_A_simple_example_of_learning_6_min.mp4
6.6 MB
01_Lecture1/04_A_simple_example_of_learning_6_min.srt
7.0 kB
01_Lecture1/04_A_simple_example_of_learning_6_min.txt
4.6 kB
01_Lecture1/05_Three_types_of_learning_8_min.mp4
9.0 MB
01_Lecture1/05_Three_types_of_learning_8_min.srt
10 kB
01_Lecture1/05_Three_types_of_learning_8_min.txt
6.8 kB
02_Lecture2/01_Types_of_neural_network_architectures_7_min.mp4
8.8 MB
02_Lecture2/01_Types_of_neural_network_architectures_7_min.pdf
493 kB
02_Lecture2/01_Types_of_neural_network_architectures_7_min.pptx
400 kB
02_Lecture2/01_Types_of_neural_network_architectures_7_min.srt
9.9 kB
02_Lecture2/01_Types_of_neural_network_architectures_7_min.txt
6.5 kB
02_Lecture2/02_Perceptrons-_The_first_generation_of_neural_networks_8_min.mp4
9.4 MB
02_Lecture2/02_Perceptrons-_The_first_generation_of_neural_networks_8_min.srt
11 kB
02_Lecture2/02_Perceptrons-_The_first_generation_of_neural_networks_8_min.txt
7.1 kB
02_Lecture2/03_A_geometrical_view_of_perceptrons_6_min.mp4
7.3 MB
02_Lecture2/03_A_geometrical_view_of_perceptrons_6_min.srt
8.3 kB
02_Lecture2/03_A_geometrical_view_of_perceptrons_6_min.txt
5.4 kB
02_Lecture2/04_Why_the_learning_works_5_min.mp4
5.9 MB
02_Lecture2/04_Why_the_learning_works_5_min.srt
6.4 kB
02_Lecture2/04_Why_the_learning_works_5_min.txt
4.2 kB
02_Lecture2/05_What_perceptrons_cant_do_15_min.mp4
17 MB
02_Lecture2/05_What_perceptrons_cant_do_15_min.srt
18 kB
02_Lecture2/05_What_perceptrons_cant_do_15_min.txt
12 kB
03_Lecture3/01_Learning_the_weights_of_a_linear_neuron_12_min.mp4
14 MB
03_Lecture3/01_Learning_the_weights_of_a_linear_neuron_12_min.pdf
535 kB
03_Lecture3/01_Learning_the_weights_of_a_linear_neuron_12_min.pptx
1.1 MB
03_Lecture3/01_Learning_the_weights_of_a_linear_neuron_12_min.srt
15 kB
03_Lecture3/01_Learning_the_weights_of_a_linear_neuron_12_min.txt
9.9 kB
03_Lecture3/02_The_error_surface_for_a_linear_neuron_5_min.mp4
5.9 MB
03_Lecture3/02_The_error_surface_for_a_linear_neuron_5_min.srt
6.3 kB
03_Lecture3/02_The_error_surface_for_a_linear_neuron_5_min.txt
4.1 kB
03_Lecture3/03_Learning_the_weights_of_a_logistic_output_neuron_4_min.mp4
4.4 MB
03_Lecture3/03_Learning_the_weights_of_a_logistic_output_neuron_4_min.srt
4.5 kB
03_Lecture3/03_Learning_the_weights_of_a_logistic_output_neuron_4_min.txt
2.9 kB
03_Lecture3/04_The_backpropagation_algorithm_12_min.mp4
13 MB
03_Lecture3/04_The_backpropagation_algorithm_12_min.pdf
3.0 MB
03_Lecture3/04_The_backpropagation_algorithm_12_min.srt
15 kB
03_Lecture3/04_The_backpropagation_algorithm_12_min.txt
9.7 kB
03_Lecture3/05_Using_the_derivatives_computed_by_backpropagation_10_min.mp4
11 MB
03_Lecture3/05_Using_the_derivatives_computed_by_backpropagation_10_min.srt
14 kB
03_Lecture3/05_Using_the_derivatives_computed_by_backpropagation_10_min.txt
8.9 kB
04_Lecture4/01_Learning_to_predict_the_next_word_13_min.mp4
14 MB
04_Lecture4/01_Learning_to_predict_the_next_word_13_min.pdf
942 kB
04_Lecture4/01_Learning_to_predict_the_next_word_13_min.pptx
1.1 MB
04_Lecture4/01_Learning_to_predict_the_next_word_13_min.srt
16 kB
04_Lecture4/01_Learning_to_predict_the_next_word_13_min.txt
11 kB
04_Lecture4/02_A_brief_diversion_into_cognitive_science_4_min.mp4
5.3 MB
04_Lecture4/02_A_brief_diversion_into_cognitive_science_4_min.srt
5.8 kB
04_Lecture4/02_A_brief_diversion_into_cognitive_science_4_min.txt
3.7 kB
04_Lecture4/03_Another_diversion-_The_softmax_output_function_7_min.mp4
8.0 MB
04_Lecture4/03_Another_diversion-_The_softmax_output_function_7_min.srt
9.1 kB
04_Lecture4/03_Another_diversion-_The_softmax_output_function_7_min.txt
5.9 kB
04_Lecture4/04_Neuro-probabilistic_language_models_8_min.mp4
8.9 MB
04_Lecture4/04_Neuro-probabilistic_language_models_8_min.pdf
137 kB
04_Lecture4/04_Neuro-probabilistic_language_models_8_min.srt
11 kB
04_Lecture4/04_Neuro-probabilistic_language_models_8_min.txt
7.0 kB
04_Lecture4/05_Ways_to_deal_with_the_large_number_of_possible_outputs_15_min.mp4
14 MB
04_Lecture4/05_Ways_to_deal_with_the_large_number_of_possible_outputs_15_min.png
151 kB
04_Lecture4/05_Ways_to_deal_with_the_large_number_of_possible_outputs_15_min.srt
18 kB
04_Lecture4/05_Ways_to_deal_with_the_large_number_of_possible_outputs_15_min.txt
12 kB
05_Lecture5/01_Why_object_recognition_is_difficult_5_min.mp4
5.4 MB
05_Lecture5/01_Why_object_recognition_is_difficult_5_min.pdf
1.6 MB
05_Lecture5/01_Why_object_recognition_is_difficult_5_min.pptx
1.7 MB
05_Lecture5/01_Why_object_recognition_is_difficult_5_min.srt
6.2 kB
05_Lecture5/01_Why_object_recognition_is_difficult_5_min.txt
4.0 kB
05_Lecture5/02_Achieving_viewpoint_invariance_6_min.mp4
6.9 MB
05_Lecture5/02_Achieving_viewpoint_invariance_6_min.srt
8.1 kB
05_Lecture5/02_Achieving_viewpoint_invariance_6_min.txt
5.2 kB
05_Lecture5/03_Convolutional_nets_for_digit_recognition_16_min.mp4
18 MB
05_Lecture5/03_Convolutional_nets_for_digit_recognition_16_min.srt
22 kB
05_Lecture5/03_Convolutional_nets_for_digit_recognition_16_min.txt
14 kB
05_Lecture5/04_Convolutional_nets_for_object_recognition_17min.mp4
23 MB
05_Lecture5/04_Convolutional_nets_for_object_recognition_17min.pdf
122 kB
05_Lecture5/04_Convolutional_nets_for_object_recognition_17min.srt
26 kB
05_Lecture5/04_Convolutional_nets_for_object_recognition_17min.txt
17 kB
05_Lecture5/04_Convolutional_nets_for_object_recognition_17min_0_hard_Gradient-based_learning_applied_to_document_recognition.pdf
933 kB
06_Lecture6/01_Overview_of_mini-batch_gradient_descent.mp4
9.6 MB
06_Lecture6/01_Overview_of_mini-batch_gradient_descent.pdf
534 kB
06_Lecture6/01_Overview_of_mini-batch_gradient_descent.pptx
657 kB
06_Lecture6/01_Overview_of_mini-batch_gradient_descent.srt
12 kB
06_Lecture6/01_Overview_of_mini-batch_gradient_descent.txt
7.8 kB
06_Lecture6/02_A_bag_of_tricks_for_mini-batch_gradient_descent.mp4
15 MB
06_Lecture6/02_A_bag_of_tricks_for_mini-batch_gradient_descent.srt
19 kB
06_Lecture6/02_A_bag_of_tricks_for_mini-batch_gradient_descent.txt
12 kB
06_Lecture6/03_The_momentum_method.mp4
9.7 MB
06_Lecture6/03_The_momentum_method.srt
11 kB
06_Lecture6/03_The_momentum_method.txt
7.2 kB
06_Lecture6/04_Adaptive_learning_rates_for_each_connection.mp4
6.6 MB
06_Lecture6/04_Adaptive_learning_rates_for_each_connection.srt
7.7 kB
06_Lecture6/04_Adaptive_learning_rates_for_each_connection.txt
5.1 kB
06_Lecture6/05_Rmsprop-_Divide_the_gradient_by_a_running_average_of_its_recent_magnitude.mp4
15 MB
06_Lecture6/05_Rmsprop-_Divide_the_gradient_by_a_running_average_of_its_recent_magnitude.srt
16 kB
06_Lecture6/05_Rmsprop-_Divide_the_gradient_by_a_running_average_of_its_recent_magnitude.txt
10 kB
07_Lecture7/01_Modeling_sequences-_A_brief_overview.mp4
20 MB
07_Lecture7/01_Modeling_sequences-_A_brief_overview.pdf
953 kB
07_Lecture7/01_Modeling_sequences-_A_brief_overview.pptx
223 kB
07_Lecture7/01_Modeling_sequences-_A_brief_overview.srt
23 kB
07_Lecture7/01_Modeling_sequences-_A_brief_overview.txt
15 kB
07_Lecture7/02_Training_RNNs_with_back_propagation.mp4
7.3 MB
07_Lecture7/02_Training_RNNs_with_back_propagation.srt
8.4 kB
07_Lecture7/02_Training_RNNs_with_back_propagation.txt
5.5 kB
07_Lecture7/03_A_toy_example_of_training_an_RNN.mp4
7.2 MB
07_Lecture7/03_A_toy_example_of_training_an_RNN.srt
7.5 kB
07_Lecture7/03_A_toy_example_of_training_an_RNN.txt
4.9 kB
07_Lecture7/04_Why_it_is_difficult_to_train_an_RNN.mp4
8.9 MB
07_Lecture7/04_Why_it_is_difficult_to_train_an_RNN.srt
9.8 kB
07_Lecture7/04_Why_it_is_difficult_to_train_an_RNN.txt
6.4 kB
07_Lecture7/05_Long-term_Short-term-memory.mp4
10 MB
07_Lecture7/05_Long-term_Short-term-memory.pdf
313 kB
07_Lecture7/05_Long-term_Short-term-memory.srt
12 kB
07_Lecture7/05_Long-term_Short-term-memory.txt
7.7 kB
08_Lecture8/01_A_brief_overview_of_Hessian_Free_optimization.mp4
16 MB
08_Lecture8/01_A_brief_overview_of_Hessian_Free_optimization.pdf
643 kB
08_Lecture8/01_A_brief_overview_of_Hessian_Free_optimization.pptx
555 kB
08_Lecture8/01_A_brief_overview_of_Hessian_Free_optimization.srt
18 kB
08_Lecture8/01_A_brief_overview_of_Hessian_Free_optimization.txt
12 kB
08_Lecture8/02_Modeling_character_strings_with_multiplicative_connections_14_mins.mp4
17 MB
08_Lecture8/02_Modeling_character_strings_with_multiplicative_connections_14_mins.srt
18 kB
08_Lecture8/02_Modeling_character_strings_with_multiplicative_connections_14_mins.txt
12 kB
08_Lecture8/03_Learning_to_predict_the_next_character_using_HF_12__mins.mp4
14 MB
08_Lecture8/03_Learning_to_predict_the_next_character_using_HF_12__mins.pdf
267 kB
08_Lecture8/03_Learning_to_predict_the_next_character_using_HF_12__mins.srt
16 kB
08_Lecture8/03_Learning_to_predict_the_next_character_using_HF_12__mins.txt
10 kB
08_Lecture8/04_Echo_State_Networks_9_min.mp4
11 MB
08_Lecture8/04_Echo_State_Networks_9_min.srt
12 kB
08_Lecture8/04_Echo_State_Networks_9_min.txt
7.9 kB
09_Lecture9/01_Overview_of_ways_to_improve_generalization_12_min.mp4
14 MB
09_Lecture9/01_Overview_of_ways_to_improve_generalization_12_min.pdf
702 kB
09_Lecture9/01_Overview_of_ways_to_improve_generalization_12_min.pptx
1.5 MB
09_Lecture9/01_Overview_of_ways_to_improve_generalization_12_min.srt
16 kB
09_Lecture9/01_Overview_of_ways_to_improve_generalization_12_min.txt
10 kB
09_Lecture9/02_Limiting_the_size_of_the_weights_6_min.mp4
7.4 MB
09_Lecture9/02_Limiting_the_size_of_the_weights_6_min.srt
8.4 kB
09_Lecture9/02_Limiting_the_size_of_the_weights_6_min.txt
5.5 kB
09_Lecture9/03_Using_noise_as_a_regularizer_7_min.mp4
8.5 MB
09_Lecture9/03_Using_noise_as_a_regularizer_7_min.srt
8.9 kB
09_Lecture9/03_Using_noise_as_a_regularizer_7_min.txt
5.8 kB
09_Lecture9/04_Introduction_to_the_full_Bayesian_approach_12_min.mp4
12 MB
09_Lecture9/04_Introduction_to_the_full_Bayesian_approach_12_min.srt
13 kB
09_Lecture9/04_Introduction_to_the_full_Bayesian_approach_12_min.txt
8.6 kB
09_Lecture9/05_The_Bayesian_interpretation_of_weight_decay_11_min.mp4
12 MB
09_Lecture9/05_The_Bayesian_interpretation_of_weight_decay_11_min.srt
13 kB
09_Lecture9/05_The_Bayesian_interpretation_of_weight_decay_11_min.txt
8.6 kB
09_Lecture9/06_MacKays_quick_and_dirty_method_of_setting_weight_costs_4_min.mp4
4.4 MB
09_Lecture9/06_MacKays_quick_and_dirty_method_of_setting_weight_costs_4_min.srt
4.4 kB
09_Lecture9/06_MacKays_quick_and_dirty_method_of_setting_weight_costs_4_min.txt
2.9 kB
10_Lecture10/01_Why_it_helps_to_combine_models_13_min.mp4
15 MB
10_Lecture10/01_Why_it_helps_to_combine_models_13_min.pdf
827 kB
10_Lecture10/01_Why_it_helps_to_combine_models_13_min.pptx
880 kB
10_Lecture10/01_Why_it_helps_to_combine_models_13_min.srt
18 kB
10_Lecture10/01_Why_it_helps_to_combine_models_13_min.txt
12 kB
10_Lecture10/02_Mixtures_of_Experts_13_min.mp4
15 MB
10_Lecture10/02_Mixtures_of_Experts_13_min.pdf
265 kB
10_Lecture10/02_Mixtures_of_Experts_13_min.srt
17 kB
10_Lecture10/02_Mixtures_of_Experts_13_min.txt
11 kB
10_Lecture10/03_The_idea_of_full_Bayesian_learning_7_min.mp4
8.4 MB
10_Lecture10/03_The_idea_of_full_Bayesian_learning_7_min.srt
10 kB
10_Lecture10/03_The_idea_of_full_Bayesian_learning_7_min.txt
6.7 kB
10_Lecture10/04_Making_full_Bayesian_learning_practical_7_min.mp4
8.1 MB
10_Lecture10/04_Making_full_Bayesian_learning_practical_7_min.srt
8.5 kB
10_Lecture10/04_Making_full_Bayesian_learning_practical_7_min.txt
5.6 kB
10_Lecture10/05_Dropout_9_min.mp4
9.7 MB
10_Lecture10/05_Dropout_9_min.pdf
1.6 MB
10_Lecture10/05_Dropout_9_min.srt
12 kB
10_Lecture10/05_Dropout_9_min.txt
7.6 kB
11_Lecture11/01_Hopfield_Nets_13_min.mp4
15 MB
11_Lecture11/01_Hopfield_Nets_13_min.pdf
694 kB
11_Lecture11/01_Hopfield_Nets_13_min.pptx
726 kB
11_Lecture11/01_Hopfield_Nets_13_min.srt
16 kB
11_Lecture11/01_Hopfield_Nets_13_min.txt
11 kB
11_Lecture11/02_Dealing_with_spurious_minima_11_min.mp4
13 MB
11_Lecture11/02_Dealing_with_spurious_minima_11_min.srt
15 kB
11_Lecture11/02_Dealing_with_spurious_minima_11_min.txt
9.8 kB
11_Lecture11/03_Hopfield_nets_with_hidden_units_10_min.mp4
11 MB
11_Lecture11/03_Hopfield_nets_with_hidden_units_10_min.srt
12 kB
11_Lecture11/03_Hopfield_nets_with_hidden_units_10_min.txt
8.1 kB
11_Lecture11/04_Using_stochastic_units_to_improv_search_11_min.mp4
12 MB
11_Lecture11/04_Using_stochastic_units_to_improv_search_11_min.srt
14 kB
11_Lecture11/04_Using_stochastic_units_to_improv_search_11_min.txt
9.1 kB
11_Lecture11/05_How_a_Boltzmann_machine_models_data_12_min.mp4
13 MB
11_Lecture11/05_How_a_Boltzmann_machine_models_data_12_min.srt
16 kB
11_Lecture11/05_How_a_Boltzmann_machine_models_data_12_min.txt
10 kB
12_Lecture12/01_Boltzmann_machine_learning_12_min.mp4
14 MB
12_Lecture12/01_Boltzmann_machine_learning_12_min.pdf
1.7 MB
12_Lecture12/01_Boltzmann_machine_learning_12_min.pptx
1.9 MB
12_Lecture12/01_Boltzmann_machine_learning_12_min.srt
16 kB
12_Lecture12/01_Boltzmann_machine_learning_12_min.txt
10 kB
12_Lecture12/02_OPTIONAL_VIDEO-_More_efficient_ways_to_get_the_statistics_15_mins.mp4
17 MB
12_Lecture12/02_OPTIONAL_VIDEO-_More_efficient_ways_to_get_the_statistics_15_mins.srt
18 kB
12_Lecture12/02_OPTIONAL_VIDEO-_More_efficient_ways_to_get_the_statistics_15_mins.txt
12 kB
12_Lecture12/03_Restricted_Boltzmann_Machines_11_min.mp4
13 MB
12_Lecture12/03_Restricted_Boltzmann_Machines_11_min.srt
14 kB
12_Lecture12/03_Restricted_Boltzmann_Machines_11_min.txt
8.9 kB
12_Lecture12/04_An_example_of_RBM_learning_7_mins.mp4
8.7 MB
12_Lecture12/04_An_example_of_RBM_learning_7_mins.srt
9.9 kB
12_Lecture12/04_An_example_of_RBM_learning_7_mins.txt
6.5 kB
12_Lecture12/05_RBMs_for_collaborative_filtering_8_mins.mp4
9.5 MB
12_Lecture12/05_RBMs_for_collaborative_filtering_8_mins.srt
11 kB
12_Lecture12/05_RBMs_for_collaborative_filtering_8_mins.txt
7.0 kB
13_Lecture13/01_The_ups_and_downs_of_back_propagation_10_min.mp4
12 MB
13_Lecture13/01_The_ups_and_downs_of_back_propagation_10_min.pdf
307 kB
13_Lecture13/01_The_ups_and_downs_of_back_propagation_10_min.pptx
415 kB
13_Lecture13/01_The_ups_and_downs_of_back_propagation_10_min.srt
14 kB
13_Lecture13/01_The_ups_and_downs_of_back_propagation_10_min.txt
8.8 kB
13_Lecture13/02_Belief_Nets_13_min.mp4
15 MB
13_Lecture13/02_Belief_Nets_13_min.srt
17 kB
13_Lecture13/02_Belief_Nets_13_min.txt
11 kB
13_Lecture13/03_Learning_sigmoid_belief_nets_12_min.mp4
14 MB
13_Lecture13/03_Learning_sigmoid_belief_nets_12_min.pdf
2.3 MB
13_Lecture13/03_Learning_sigmoid_belief_nets_12_min.srt
15 kB
13_Lecture13/03_Learning_sigmoid_belief_nets_12_min.txt
9.5 kB
13_Lecture13/04_The_wake-sleep_algorithm_13_min.mp4
16 MB
13_Lecture13/04_The_wake-sleep_algorithm_13_min.pdf
255 kB
13_Lecture13/04_The_wake-sleep_algorithm_13_min.srt
17 kB
13_Lecture13/04_The_wake-sleep_algorithm_13_min.txt
11 kB
14_Lecture14/01_Learning_layers_of_features_by_stacking_RBMs_17_min.mp4
20 MB
14_Lecture14/01_Learning_layers_of_features_by_stacking_RBMs_17_min.pdf
1.1 MB
14_Lecture14/01_Learning_layers_of_features_by_stacking_RBMs_17_min.pptx
1.2 MB
14_Lecture14/01_Learning_layers_of_features_by_stacking_RBMs_17_min.srt
23 kB
14_Lecture14/01_Learning_layers_of_features_by_stacking_RBMs_17_min.txt
15 kB
14_Lecture14/01_Learning_layers_of_features_by_stacking_RBMs_17_min_0_Self-taught_learning-_transfer_learning_from_unlabeled_data.pdf
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