Edureka Practical Deep Learning With Python | D0FACF94C5D4862B6C9BDC166BDD16DFFCC1D420

Edureka Practical Deep Learning With Python

Name	Edureka - Practical Deep Learning With Python	DOWNLOAD Copy Link
Total Size	2.9 GB
Total Files	93
Last Seen	2025-03-11 23:55
Hash	D0FACF94C5D4862B6C9BDC166BDD16DFFCC1D420

/.../01-Environment_Set_Up_And_Configuration/
01-welcome_to_practical_deep_learning_with_python_instructions.html	7.4 KB
02-course_introduction.mp4	29.3 MB
03-environment_configuration.mp4	22.9 MB
04-system_requirements_and_pre_requisite_for_studying_deep_learning_instructions.html	4.6 KB
/.../02-Essentials_Of_Deep_Learning/
01-machine_learning_vs_deep_learning.mp4	35.9 MB
02-what_is_deep_learning.mp4	21.3 MB
03-neural_networks.mp4	44.2 MB
04-artificial_neural_network_ann.mp4	25.6 MB
05-ann_types_and_applications.mp4	18.6 MB
06-forward_propagation.mp4	21.6 MB
07-perceptron.mp4	32.4 MB
08-learning_rate.mp4	30.7 MB
09-what_is_activation_function.mp4	18.7 MB
10-activation_function_and_its_types.mp4	24.6 MB
11-importance_of_epoch.mp4	26.0 MB
12-single_layer_perceptron_define_sigmoid_function.mp4	46.1 MB
13-single_layer_perceptron_decision_boundary.mp4	80.9 MB
14-learning_rate_in_deep_learning_instructions.html	4.0 KB
/.../03-Building_Perceptron_And_Its_Working/
01-limitations_of_single_layered_perceptron.mp4	11.6 MB
02-multi_layered_perceptron.mp4	12.6 MB
03-what_is_backpropagation.mp4	10.8 MB
04-backpropagation.mp4	17.8 MB
05-demonstration_building_a_simple_neural_network.mp4	42.9 MB
06-demonstration_understanding_how_backpropagation_has_worked.mp4	42.4 MB
07-demonstration_handwritten_digits_classification_data_preprocessing.mp4	43.8 MB
08-demonstration_handwritten_digits_classification_designing_the_model.mp4	76.8 MB
09-demonstration_handwritten_digits_classification_optimizing_the_model.mp4	93.1 MB
10-hebbian_learning_algorithm_instructions.html	27.9 KB
/.../04-Module_Wrap_Up_And_Assessment/
01-summary_of_deep_learning_components.mp4	38.1 MB
/.../01-Convolutional_Neural_Network/
01-limitations_of_mlp.mp4	29.3 MB
02-mlp_limitations_resolving_the_issue_with_cnn.mp4	22.6 MB
03-visual_cortex_and_cnn.mp4	33.1 MB
04-convolutional_layer.mp4	33.5 MB
05-working_of_convolutional_layer.mp4	33.5 MB
06-demonstration_load_and_preprocess_the_data.mp4	44.1 MB
07-demonstration_designing_the_model.mp4	55.4 MB
08-demonstration_building_the_cnn_model.mp4	39.8 MB
09-demonstration_model_accuracy.mp4	22.5 MB
10-demonstration_adding_more_layers.mp4	65.4 MB
11-demonstration_building_basic_cnn_model_with_new_parameters.mp4	82.0 MB
12-demonstration_pre_trained_model.mp4	39.2 MB
13-why_convolutions_are_important_instructions.html	2.1 KB
/.../02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/
01-classification_and_object_detection.mp4	31.3 MB
02-introduction_to_rcnn.mp4	33.0 MB
03-r_cnn_bounding_box_regression.mp4	13.1 MB
04-pre_trained_model.mp4	30.5 MB
05-fast_regional_cnn.mp4	33.7 MB
06-demonstration_creating_base_variables_and_loading_the_model.mp4	38.8 MB
07-demonstration_training_the_model_and_visualizing_the_predictions.mp4	56.2 MB
08-demonstration_svm_as_a_classifier.mp4	24.5 MB
09-svm_classifier_in_object_detection_instructions.html	4.4 KB
/.../03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/
01-fast_rcnn_limitations.mp4	26.1 MB
02-advent_of_faster_r_cnn.mp4	26.5 MB
03-tensorflow_hub.mp4	21.3 MB
04-demonstration_object_detection_with_faster_rcnn_pretrained_model_setup.mp4	78.3 MB
05-demonstration_object_detection_with_faster_rcnn_building_the_model.mp4	86.9 MB
06-faster_r_cnn_architecture_instructions.html	6.1 KB
/.../04-Module_Wrap_Up_And_Assessment/
01-summary_of_cnn_in_deep_learning.mp4	14.0 MB
02-summary_of_faster_rcnn.mp4	23.6 MB
/.../01-Working_Of_Recurrent_Neural_Networks_Rnn/
01-rnn_fundamentals.mp4	21.5 MB
02-rnn_architecture.mp4	23.7 MB
03-rnn_architecture_workflow.mp4	30.3 MB
04-implementing_rnn.mp4	30.3 MB
05-demonstration_rnn_dataset_preparation.mp4	65.1 MB
06-demonstration_rnn_building_the_model.mp4	65.4 MB
07-recurrent_neural_networks_rnns_in_deep_learning_instructions.html	20.1 KB
/.../02-Lstm_Architecture/
01-basics_of_lstm.mp4	29.7 MB
02-lstm_structure.mp4	25.4 MB
03-forget_gate_and_input_gate.mp4	21.9 MB
04-output_gate.mp4	14.8 MB
05-importance_of_lstm_architecture.mp4	24.2 MB
06-types_of_lstm.mp4	20.1 MB
07-demonstration_next_word_prediction_processing_the_corpus.mp4	52.6 MB
08-demonstration_next_word_prediction_layers.mp4	61.8 MB
09-demonstration_next_word_prediction_model_compilation_and_prediction.mp4	101.3 MB
10-attention_based_lstm_long_short_term_memory_instructions.html	7.6 KB
11-capsule_networks_in_deep_learning_instructions.html	4.3 KB
/.../03-Module_Optimization_And_Compilation/
01-improving_a_model.mp4	34.5 MB
02-model_optimization.mp4	22.9 MB
03-using_adam_optimizer.mp4	33.5 MB
04-model_compilation.mp4	15.1 MB
05-model_compilation_with_popular_frameworks.mp4	28.7 MB
06-demonstration_model_compilation_preparing_the_dataset.mp4	58.2 MB
07-demonstration_building_and_compiling_model.mp4	48.5 MB
08-demonstration_from_rmsprop_to_adam.mp4	47.4 MB
09-model_optimizers_beyond_adam_instructions.html	89.4 KB
/.../04-Module_Wrap_Up_And_Assessment/
01-summary_of_deep_learning_with_rnn_and_lstm_with_model_optimization.mp4	34.5 MB
/04-Course_Wrap_Up_And_Assessment/
01-course_summary_for_practical_deep_learning_with_python.mp4	24.5 MB
02-practice_project_mnist_fashion_dataset_analysis_instructions.html	65.5 KB
/.../01-Module_3_Datasets/
deeplearning.txt	49.6 KB
history.p	0.4 KB
next_word_model.keras	10.2 MB
/.../02-Module_2_Datasets/
resources.html	67.3 KB
Total files 93