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Language:
English
Total Size:
2.7 GB
Info Hash:
D0FACF94C5D4862B6C9BDC166BDD16DFFCC1D420
Added By:
Added:
March 1, 2025, 1:59 p.m.
Stats:
|
(Last updated: Feb. 15, 2026, 12:08 p.m.)
| File | Size |
|---|---|
| 01-welcome_to_practical_deep_learning_with_python_instructions.html | 7.2 KB |
| 02-course_introduction.mp4 | 28.0 MB |
| 03-environment_configuration.mp4 | 21.8 MB |
| 04-system_requirements_and_pre_requisite_for_studying_deep_learning_instructions.html | 4.5 KB |
| 01-machine_learning_vs_deep_learning.mp4 | 34.3 MB |
| 02-what_is_deep_learning.mp4 | 20.3 MB |
| 03-neural_networks.mp4 | 42.2 MB |
| 04-artificial_neural_network_ann.mp4 | 24.4 MB |
| 05-ann_types_and_applications.mp4 | 17.8 MB |
| 06-forward_propagation.mp4 | 20.6 MB |
| 07-perceptron.mp4 | 30.9 MB |
| 08-learning_rate.mp4 | 29.3 MB |
| 09-what_is_activation_function.mp4 | 17.8 MB |
| 10-activation_function_and_its_types.mp4 | 23.4 MB |
| 11-importance_of_epoch.mp4 | 24.8 MB |
| 12-single_layer_perceptron_define_sigmoid_function.mp4 | 44.0 MB |
| 13-single_layer_perceptron_decision_boundary.mp4 | 77.2 MB |
| 14-learning_rate_in_deep_learning_instructions.html | 3.9 KB |
| 01-limitations_of_single_layered_perceptron.mp4 | 11.1 MB |
| 02-multi_layered_perceptron.mp4 | 12.0 MB |
| 03-what_is_backpropagation.mp4 | 10.3 MB |
| 04-backpropagation.mp4 | 17.0 MB |
| 05-demonstration_building_a_simple_neural_network.mp4 | 40.9 MB |
| 06-demonstration_understanding_how_backpropagation_has_worked.mp4 | 40.5 MB |
| 07-demonstration_handwritten_digits_classification_data_preprocessing.mp4 | 41.8 MB |
| 08-demonstration_handwritten_digits_classification_designing_the_model.mp4 | 73.2 MB |
| 09-demonstration_handwritten_digits_classification_optimizing_the_model.mp4 | 88.8 MB |
| 10-hebbian_learning_algorithm_instructions.html | 27.3 KB |
| 01-summary_of_deep_learning_components.mp4 | 36.3 MB |
| 01-limitations_of_mlp.mp4 | 27.9 MB |
| 02-mlp_limitations_resolving_the_issue_with_cnn.mp4 | 21.5 MB |
| 03-visual_cortex_and_cnn.mp4 | 31.6 MB |
| 04-convolutional_layer.mp4 | 32.0 MB |
| 05-working_of_convolutional_layer.mp4 | 32.0 MB |
| 06-demonstration_load_and_preprocess_the_data.mp4 | 42.0 MB |
| 07-demonstration_designing_the_model.mp4 | 52.8 MB |
| 08-demonstration_building_the_cnn_model.mp4 | 38.0 MB |
| 09-demonstration_model_accuracy.mp4 | 21.5 MB |
| 10-demonstration_adding_more_layers.mp4 | 62.4 MB |
| 11-demonstration_building_basic_cnn_model_with_new_parameters.mp4 | 78.2 MB |
| 12-demonstration_pre_trained_model.mp4 | 37.4 MB |
| 13-why_convolutions_are_important_instructions.html | 2.1 KB |
| 01-classification_and_object_detection.mp4 | 29.8 MB |
| 02-introduction_to_rcnn.mp4 | 31.5 MB |
| 03-r_cnn_bounding_box_regression.mp4 | 12.5 MB |
| 04-pre_trained_model.mp4 | 29.0 MB |
| 05-fast_regional_cnn.mp4 | 32.1 MB |
| 06-demonstration_creating_base_variables_and_loading_the_model.mp4 | 37.0 MB |
| 07-demonstration_training_the_model_and_visualizing_the_predictions.mp4 | 53.6 MB |
| 08-demonstration_svm_as_a_classifier.mp4 | 23.4 MB |
| 09-svm_classifier_in_object_detection_instructions.html | 4.3 KB |
| 01-fast_rcnn_limitations.mp4 | 24.9 MB |
| 02-advent_of_faster_r_cnn.mp4 | 25.2 MB |
| 03-tensorflow_hub.mp4 | 20.3 MB |
| 04-demonstration_object_detection_with_faster_rcnn_pretrained_model_setup.mp4 | 74.7 MB |
| 05-demonstration_object_detection_with_faster_rcnn_building_the_model.mp4 | 82.9 MB |
| 06-faster_r_cnn_architecture_instructions.html | 5.9 KB |
| 01-summary_of_cnn_in_deep_learning.mp4 | 13.3 MB |
| 02-summary_of_faster_rcnn.mp4 | 22.5 MB |
| 01-rnn_fundamentals.mp4 | 20.5 MB |
| 02-rnn_architecture.mp4 | 22.6 MB |
| 03-rnn_architecture_workflow.mp4 | 28.9 MB |
| 04-implementing_rnn.mp4 | 28.9 MB |
| 05-demonstration_rnn_dataset_preparation.mp4 | 62.0 MB |
| 06-demonstration_rnn_building_the_model.mp4 | 62.4 MB |
| 07-recurrent_neural_networks_rnns_in_deep_learning_instructions.html | 19.6 KB |
| 01-basics_of_lstm.mp4 | 28.4 MB |
| 02-lstm_structure.mp4 | 24.2 MB |
| 03-forget_gate_and_input_gate.mp4 | 20.9 MB |
| 04-output_gate.mp4 | 14.1 MB |
| 05-importance_of_lstm_architecture.mp4 | 23.0 MB |
| 06-types_of_lstm.mp4 | 19.2 MB |
| 07-demonstration_next_word_prediction_processing_the_corpus.mp4 | 50.2 MB |
| 08-demonstration_next_word_prediction_layers.mp4 | 58.9 MB |
| 09-demonstration_next_word_prediction_model_compilation_and_prediction.mp4 | 96.6 MB |
| 10-attention_based_lstm_long_short_term_memory_instructions.html | 7.4 KB |
| 11-capsule_networks_in_deep_learning_instructions.html | 4.2 KB |
| 01-improving_a_model.mp4 | 32.9 MB |
| 02-model_optimization.mp4 | 21.8 MB |
| 03-using_adam_optimizer.mp4 | 32.0 MB |
| 04-model_compilation.mp4 | 14.4 MB |
| 05-model_compilation_with_popular_frameworks.mp4 | 27.3 MB |
| 06-demonstration_model_compilation_preparing_the_dataset.mp4 | 55.5 MB |
| 07-demonstration_building_and_compiling_model.mp4 | 46.3 MB |
| 08-demonstration_from_rmsprop_to_adam.mp4 | 45.2 MB |
| 09-model_optimizers_beyond_adam_instructions.html | 87.4 KB |
| 01-summary_of_deep_learning_with_rnn_and_lstm_with_model_optimization.mp4 | 32.9 MB |
| 01-course_summary_for_practical_deep_learning_with_python.mp4 | 23.4 MB |
| 02-practice_project_mnist_fashion_dataset_analysis_instructions.html | 64.0 KB |
| deeplearning.txt | 48.5 KB |
| history.p | 436 bytes |
| next_word_model.keras | 9.8 MB |
| resources.html | 65.7 KB |
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SOURCE: Edureka Practical Deep Learning With Python
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