Download Edureka - Practical Deep Learning With Python Torrent

Torrent Contents Size: 2.7 GB

Edureka - Practical Deep Learning With Python

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01-basics_of_lstm.mp4	MP4	28.4 MB
01-classification_and_object_detection.mp4	MP4	29.8 MB
01-course_summary_for_practical_deep_learning_with_python.mp4	MP4	23.4 MB
01-fast_rcnn_limitations.mp4	MP4	24.9 MB
01-improving_a_model.mp4	MP4	32.9 MB
01-limitations_of_mlp.mp4	MP4	27.9 MB
01-limitations_of_single_layered_perceptron.mp4	MP4	11.1 MB
01-machine_learning_vs_deep_learning.mp4	MP4	34.3 MB
01-rnn_fundamentals.mp4	MP4	20.5 MB
01-summary_of_cnn_in_deep_learning.mp4	MP4	13.3 MB
01-summary_of_deep_learning_components.mp4	MP4	36.3 MB
01-summary_of_deep_learning_with_rnn_and_lstm_with_model_optimization.mp4	MP4	32.9 MB
01-welcome_to_practical_deep_learning_with_python_instructions.html	HTML	7.2 KB
02-advent_of_faster_r_cnn.mp4	MP4	25.2 MB
02-course_introduction.mp4	MP4	28 MB
02-introduction_to_rcnn.mp4	MP4	31.5 MB
02-lstm_structure.mp4	MP4	24.2 MB
02-mlp_limitations_resolving_the_issue_with_cnn.mp4	MP4	21.5 MB
02-model_optimization.mp4	MP4	21.8 MB
02-multi_layered_perceptron.mp4	MP4	12 MB
02-practice_project_mnist_fashion_dataset_analysis_instructions.html	HTML	64 KB
02-rnn_architecture.mp4	MP4	22.6 MB
02-summary_of_faster_rcnn.mp4	MP4	22.5 MB
02-what_is_deep_learning.mp4	MP4	20.3 MB
03-environment_configuration.mp4	MP4	21.8 MB
03-forget_gate_and_input_gate.mp4	MP4	20.9 MB
03-neural_networks.mp4	MP4	42.2 MB
03-r_cnn_bounding_box_regression.mp4	MP4	12.5 MB
03-rnn_architecture_workflow.mp4	MP4	28.9 MB
03-tensorflow_hub.mp4	MP4	20.3 MB
03-using_adam_optimizer.mp4	MP4	32 MB
03-visual_cortex_and_cnn.mp4	MP4	31.6 MB
03-what_is_backpropagation.mp4	MP4	10.3 MB
04-artificial_neural_network_ann.mp4	MP4	24.4 MB
04-backpropagation.mp4	MP4	17 MB
04-convolutional_layer.mp4	MP4	32 MB
04-demonstration_object_detection_with_faster_rcnn_pretrained_model_setup.mp4	MP4	74.7 MB
04-implementing_rnn.mp4	MP4	28.9 MB
04-model_compilation.mp4	MP4	14.4 MB
04-output_gate.mp4	MP4	14.1 MB
04-pre_trained_model.mp4	MP4	29 MB
04-system_requirements_and_pre_requisite_for_studying_deep_learning_instructions.html	HTML	4.5 KB
05-ann_types_and_applications.mp4	MP4	17.8 MB
05-demonstration_building_a_simple_neural_network.mp4	MP4	40.9 MB
05-demonstration_object_detection_with_faster_rcnn_building_the_model.mp4	MP4	82.9 MB
05-demonstration_rnn_dataset_preparation.mp4	MP4	62 MB
05-fast_regional_cnn.mp4	MP4	32.1 MB
05-importance_of_lstm_architecture.mp4	MP4	23 MB
05-model_compilation_with_popular_frameworks.mp4	MP4	27.3 MB
05-working_of_convolutional_layer.mp4	MP4	32 MB
06-demonstration_creating_base_variables_and_loading_the_model.mp4	MP4	37 MB
06-demonstration_load_and_preprocess_the_data.mp4	MP4	42 MB
06-demonstration_model_compilation_preparing_the_dataset.mp4	MP4	55.5 MB
06-demonstration_rnn_building_the_model.mp4	MP4	62.4 MB
06-demonstration_understanding_how_backpropagation_has_worked.mp4	MP4	40.5 MB
06-faster_r_cnn_architecture_instructions.html	HTML	5.9 KB
06-forward_propagation.mp4	MP4	20.6 MB
06-types_of_lstm.mp4	MP4	19.2 MB
07-demonstration_building_and_compiling_model.mp4	MP4	46.3 MB
07-demonstration_designing_the_model.mp4	MP4	52.8 MB
07-demonstration_handwritten_digits_classification_data_preprocessing.mp4	MP4	41.8 MB
07-demonstration_next_word_prediction_processing_the_corpus.mp4	MP4	50.2 MB
07-demonstration_training_the_model_and_visualizing_the_predictions.mp4	MP4	53.6 MB
07-perceptron.mp4	MP4	30.9 MB
07-recurrent_neural_networks_rnns_in_deep_learning_instructions.html	HTML	19.6 KB
08-demonstration_building_the_cnn_model.mp4	MP4	38 MB
08-demonstration_from_rmsprop_to_adam.mp4	MP4	45.2 MB
08-demonstration_handwritten_digits_classification_designing_the_model.mp4	MP4	73.2 MB
08-demonstration_next_word_prediction_layers.mp4	MP4	58.9 MB
08-demonstration_svm_as_a_classifier.mp4	MP4	23.4 MB
08-learning_rate.mp4	MP4	29.3 MB
09-demonstration_handwritten_digits_classification_optimizing_the_model.mp4	MP4	88.8 MB
09-demonstration_model_accuracy.mp4	MP4	21.5 MB
09-demonstration_next_word_prediction_model_compilation_and_prediction.mp4	MP4	96.6 MB
09-model_optimizers_beyond_adam_instructions.html	HTML	87.4 KB
09-svm_classifier_in_object_detection_instructions.html	HTML	4.3 KB
09-what_is_activation_function.mp4	MP4	17.8 MB
10-activation_function_and_its_types.mp4	MP4	23.4 MB
10-attention_based_lstm_long_short_term_memory_instructions.html	HTML	7.4 KB
10-demonstration_adding_more_layers.mp4	MP4	62.4 MB
10-hebbian_learning_algorithm_instructions.html	HTML	27.3 KB
11-capsule_networks_in_deep_learning_instructions.html	HTML	4.2 KB
11-demonstration_building_basic_cnn_model_with_new_parameters.mp4	MP4	78.2 MB
11-importance_of_epoch.mp4	MP4	24.8 MB
12-demonstration_pre_trained_model.mp4	MP4	37.4 MB
12-single_layer_perceptron_define_sigmoid_function.mp4	MP4	44 MB
13-single_layer_perceptron_decision_boundary.mp4	MP4	77.2 MB
13-why_convolutions_are_important_instructions.html	HTML	2.1 KB
14-learning_rate_in_deep_learning_instructions.html	HTML	3.9 KB
deeplearning.txt	TXT	48.5 KB
history.p	P	409.6 B
next_word_model.keras	KERAS	9.8 MB
resources.html	HTML	65.7 KB

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Edureka - Practical Deep Learning With Python

Torrent Contents Size: 2.7 GB

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