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Edureka - Practical Deep Learning With Python

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2.7 GB
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Files
93
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Description
Welcome to the Practical Deep Learning with Python course, where you'll gain hands-on experience with cutting-edge deep learning techniques to model and analyze complex datasets. Unlock the power of deep learning to solve real-world problems and uncover actionable insights from massive data volumes. This course explores industry-specific applications and equips you with the practical skills needed to build and optimize advanced models.


By the end of this course, you’ll be able to:

- Describe the foundational components of deep learning models and their significance in artificial intelligence.

- Illustrate the working of CNNs, R-CNNs, and Faster R-CNNs for object detection and related applications.

- Understand the limitations of Perceptrons and how Multi-Layer Perceptrons (MLPs) address them.

- Implement Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) architectures for sequential data analysis.

- Optimize and evaluate deep learning models to achieve higher accuracy and efficiency.


This course is designed for data scientists, machine learning engineers, and AI enthusiasts with a foundational knowledge of Python and machine learning who aim to expand their expertise in deep learning.

File list
  • Edureka - Practical Deep Learning With Python
  • 01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/01-welcome_to_practical_deep_learning_with_python_instructions.html 7.2 KB
  • 01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/02-course_introduction.mp4 28 MB
  • 01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/03-environment_configuration.mp4 21.8 MB
  • 01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/04-system_requirements_and_pre_requisite_for_studying_deep_learning_instructions.html 4.5 KB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/01-machine_learning_vs_deep_learning.mp4 34.3 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/02-what_is_deep_learning.mp4 20.3 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/03-neural_networks.mp4 42.2 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/04-artificial_neural_network_ann.mp4 24.4 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/05-ann_types_and_applications.mp4 17.8 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/06-forward_propagation.mp4 20.6 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/07-perceptron.mp4 30.9 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/08-learning_rate.mp4 29.3 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/09-what_is_activation_function.mp4 17.8 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/10-activation_function_and_its_types.mp4 23.4 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/11-importance_of_epoch.mp4 24.8 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/12-single_layer_perceptron_define_sigmoid_function.mp4 44 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/13-single_layer_perceptron_decision_boundary.mp4 77.2 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/14-learning_rate_in_deep_learning_instructions.html 3.9 KB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/01-limitations_of_single_layered_perceptron.mp4 11.1 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/02-multi_layered_perceptron.mp4 12 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/03-what_is_backpropagation.mp4 10.3 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/04-backpropagation.mp4 17 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/05-demonstration_building_a_simple_neural_network.mp4 40.9 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/06-demonstration_understanding_how_backpropagation_has_worked.mp4 40.5 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/07-demonstration_handwritten_digits_classification_data_preprocessing.mp4 41.8 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/08-demonstration_handwritten_digits_classification_designing_the_model.mp4 73.2 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/09-demonstration_handwritten_digits_classification_optimizing_the_model.mp4 88.8 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/10-hebbian_learning_algorithm_instructions.html 27.3 KB
  • 01-Deep_Learning_Components/04-Module_Wrap_Up_And_Assessment/01-summary_of_deep_learning_components.mp4 36.3 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/01-limitations_of_mlp.mp4 27.9 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/02-mlp_limitations_resolving_the_issue_with_cnn.mp4 21.5 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/03-visual_cortex_and_cnn.mp4 31.6 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/04-convolutional_layer.mp4 32 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/05-working_of_convolutional_layer.mp4 32 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/06-demonstration_load_and_preprocess_the_data.mp4 42 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/07-demonstration_designing_the_model.mp4 52.8 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/08-demonstration_building_the_cnn_model.mp4 38 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/09-demonstration_model_accuracy.mp4 21.5 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/10-demonstration_adding_more_layers.mp4 62.4 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/11-demonstration_building_basic_cnn_model_with_new_parameters.mp4 78.2 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/12-demonstration_pre_trained_model.mp4 37.4 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/13-why_convolutions_are_important_instructions.html 2.1 KB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/01-classification_and_object_detection.mp4 29.8 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/02-introduction_to_rcnn.mp4 31.5 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/03-r_cnn_bounding_box_regression.mp4 12.5 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/04-pre_trained_model.mp4 29 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/05-fast_regional_cnn.mp4 32.1 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/06-demonstration_creating_base_variables_and_loading_the_model.mp4 37 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/07-demonstration_training_the_model_and_visualizing_the_predictions.mp4 53.6 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/08-demonstration_svm_as_a_classifier.mp4 23.4 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/09-svm_classifier_in_object_detection_instructions.html 4.3 KB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/01-fast_rcnn_limitations.mp4 24.9 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/02-advent_of_faster_r_cnn.mp4 25.2 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/03-tensorflow_hub.mp4 20.3 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/04-demonstration_object_detection_with_faster_rcnn_pretrained_model_setup.mp4 74.7 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/05-demonstration_object_detection_with_faster_rcnn_building_the_model.mp4 82.9 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/06-faster_r_cnn_architecture_instructions.html 5.9 KB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/04-Module_Wrap_Up_And_Assessment/01-summary_of_cnn_in_deep_learning.mp4 13.3 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/04-Module_Wrap_Up_And_Assessment/02-summary_of_faster_rcnn.mp4 22.5 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/01-rnn_fundamentals.mp4 20.5 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/02-rnn_architecture.mp4 22.6 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/03-rnn_architecture_workflow.mp4 28.9 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/04-implementing_rnn.mp4 28.9 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/05-demonstration_rnn_dataset_preparation.mp4 62 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/06-demonstration_rnn_building_the_model.mp4 62.4 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/07-recurrent_neural_networks_rnns_in_deep_learning_instructions.html 19.6 KB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/01-basics_of_lstm.mp4 28.4 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/02-lstm_structure.mp4 24.2 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/03-forget_gate_and_input_gate.mp4 20.9 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/04-output_gate.mp4 14.1 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/05-importance_of_lstm_architecture.mp4 23 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/06-types_of_lstm.mp4 19.2 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/07-demonstration_next_word_prediction_processing_the_corpus.mp4 50.2 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/08-demonstration_next_word_prediction_layers.mp4 58.9 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/09-demonstration_next_word_prediction_model_compilation_and_prediction.mp4 96.6 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/10-attention_based_lstm_long_short_term_memory_instructions.html 7.4 KB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/11-capsule_networks_in_deep_learning_instructions.html 4.2 KB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/01-improving_a_model.mp4 32.9 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/02-model_optimization.mp4 21.8 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/03-using_adam_optimizer.mp4 32 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/04-model_compilation.mp4 14.4 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/05-model_compilation_with_popular_frameworks.mp4 27.3 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/06-demonstration_model_compilation_preparing_the_dataset.mp4 55.5 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/07-demonstration_building_and_compiling_model.mp4 46.3 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/08-demonstration_from_rmsprop_to_adam.mp4 45.2 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/09-model_optimizers_beyond_adam_instructions.html 87.4 KB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/04-Module_Wrap_Up_And_Assessment/01-summary_of_deep_learning_with_rnn_and_lstm_with_model_optimization.mp4 32.9 MB
  • 04-Course_Wrap_Up_And_Assessment/01-course_summary_for_practical_deep_learning_with_python.mp4 23.4 MB
  • 04-Course_Wrap_Up_And_Assessment/02-practice_project_mnist_fashion_dataset_analysis_instructions.html 64 KB
  • Resources/01-Module_3_Datasets/deeplearning.txt 48.5 KB
  • Resources/01-Module_3_Datasets/history.p 436 B
  • Resources/01-Module_3_Datasets/next_word_model.keras 9.8 MB
  • Resources/02-Module_2_Datasets/resources.html 65.7 KB

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