文件名称：Google Brain Hugo Larochelle「Neural Networks」课件.zip（无密码）
文件大小：196.35MB
文件格式：ZIP
更新时间：2022-09-12 06:10:02
Neural Networks 神经网络 机器学习 人工智能
Google Brain Hugo Larochelle「Neural Networks」课件.zip（无密码） Google Brain Hugo Larochelle「Neural Networks」课件.zip（无密码）
【文件预览】：
Google Brain Hugo Larochelle「Neural Networks」课件
----6_02_loss_function.pdf(2.5MB)
----3_08_markov_network.pdf(4.9MB)
----10_05_language_modeling.pdf(425KB)
----9_02_local_connectivity.pdf(744KB)
----1_05_capacity_of_neural_network.pdf(2.27MB)
----5_03_free_energy.pdf(1.39MB)
----9_06_convolutional_network.pdf(796KB)
----5_01_definition.pdf(1.96MB)
----5_04_contrastive_divergence.pdf(1.66MB)
----10_08_word_tagging.pdf(829KB)
----7_02_difficulty_of_training.pdf(2.49MB)
----10_06_neural_network_language_model.pdf(1.74MB)
----10_02_preprocessing.pdf(409KB)
----7_08_variational_bound.pdf(3.48MB)
----8_06_online_dictionary_learning_algorithm.pdf(1.76MB)
----3_10_belief_propagation.pdf(7.45MB)
----4_08_pseudolikelihood.pdf(1.04MB)
----8_02_inference_ISTA_algorithm.pdf(4.79MB)
----1_02_activation_function.pdf(1.9MB)
----3_07_factors_sufficient_statistics_linear_crf.pdf(1.62MB)
----5_05_contrastive_divergence_parameter_update.pdf(1.9MB)
----7_06_deep_autoencoder.pdf(660KB)
----5_07_example.pdf(960KB)
----5_02_inference.pdf(1.97MB)
----2_08_regularization.pdf(3.22MB)
----4_05_maximum-entropy_markov_model.pdf(2.63MB)
----2_03_output_layer_gradient.pdf(4.67MB)
----5_08_extensions.pdf(2.06MB)
----10_04_word_representations.pdf(838KB)
----3_06_performing_classification.pdf(3.66MB)
----10_12_merging_representations.pdf(690KB)
----3_05_computing_marginals.pdf(1.12MB)
----4_06_hidden_markov_model.pdf(2.48MB)
----2_04_hidden_layer_gradient.pdf(5.77MB)
----7_01_motivation.pdf(3.36MB)
----8_05_dictionary_learning_algorithm.pdf(1.45MB)
----10_11_recursive_network.pdf(528KB)
----1_06_biological_inspiration.pdf(3.24MB)
----8_03_dictionary_update_projected_gradient_descent.pdf(2.11MB)
----7_04_example.pdf(4.05MB)
----9_07_object_recognition.pdf(5.67MB)
----2_10_model_selection.pdf(894KB)
----6_05_undercomplete_vs_overcomplete_hidden_layer.pdf(751KB)
----9_10_convolutional_rbm.pdf(2.5MB)
----8_09_relationship_with_V1.pdf(3.2MB)
----4_04_discriminative_vs_generative.pdf(751KB)
----8_08_feature_extraction.pdf(1.55MB)
----9_03_parameter_sharing.pdf(3.41MB)
----7_07_deep_belief_network.pdf(2MB)
----10_03_one-hot_encoding.pdf(265KB)
----9_08_example.pdf(1.71MB)
----7_09_dbn_pretraining.pdf(2.31MB)
----6_06_denoising_autoencoder.pdf(6.23MB)
----8_04_dictionary_update_block-coordinate_descent.pdf(2.42MB)
----2_05_activation_function_derivative.pdf(2.84MB)
----6_01_definition.pdf(747KB)
----3_03_context_window.pdf(2.91MB)
----3_04_computing_partition_function.pdf(6.17MB)
----10_14_recursive_network_training.pdf(3.54MB)
----4_07_general_crf.pdf(1.22MB)
----8_01_definition.pdf(2.18MB)
----8_07_ZCA_preprocessing.pdf(1.12MB)
----10_07_hierarchical_output_layer.pdf(1015KB)
----9_04_discrete_convolution.pdf(3.3MB)
----6_04_linear_autoencoder.pdf(5.04MB)
----7_03_unsupervised_pretraining.pdf(2.41MB)
----10_10_multitask_learning.pdf(1015KB)
----3_02_linear_chain_crf.pdf(2.13MB)
----3_09_factor_graph.pdf(3.94MB)
----2_01_empirical_risk_minimization.pdf(4.57MB)
----5_06_persistent_CD.pdf(846KB)
----6_03_example.pdf(1.07MB)
----10_09_convolutional_network.pdf(826KB)
----7_05_dropout.pdf(3.46MB)
----9_09_data_set_expansion.pdf(1.09MB)
----3_01_motivation.pdf(2.56MB)
----2_09_parameter_initialization.pdf(2.66MB)
----4_03_pairwise_log-factor_gradient.pdf(2.63MB)
----10_13_tree_inference.pdf(1.6MB)
----2_11_optimization.pdf(3.54MB)
----2_02_loss_function.pdf(2.64MB)
----9_05_pooling_and_subsampling.pdf(2.95MB)
----2_07_backpropagation.pdf(6.45MB)
----1_01_artificial_neuron.pdf(1.65MB)
----9_01.motivation.pdf(454KB)
----4_02_unary_log-factor_gradient.pdf(4.97MB)
----4_01_loss_function.pdf(3.9MB)
----1_04_multilayer_neural_network.pdf(3.45MB)
----10_01_motivation.pdf(148KB)
----6_07_contractive_autoencoder.pdf(1.72MB)
----2_06_parameter_gradient.pdf(4.46MB)
----1_03_capacity_of_single_neuron.pdf(1.14MB)