[OneHack.Us] Coursera - Practical Deep Learning With Python 2025

磁力链接/BT种子名称

[OneHack.Us] Coursera - Practical Deep Learning With Python 2025

磁力链接/BT种子简介

种子哈希：c7bb387e940a369d54e1c25a892b00661cb93b3b
文件大小： 2.66G
已经下载：1332次
下载速度：极快
收录时间：2025-03-16
最近下载：2025-09-04

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:C7BB387E940A369D54E1C25A892B00661CB93B3B
推荐使用PIKPAK网盘下载资源，10TB超大空间，不限制资源，无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 世界之窗 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 极乐禁地 91短视频 她趣 TikTok成人版 PornHub 听泉鉴鲍 草榴社区 哆哔涩漫 呦乐园 萝莉岛

最近搜索

文件列表

  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/09-demonstration_next_word_prediction_model_compilation_and_prediction.mp4 101.3 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/09-demonstration_handwritten_digits_classification_optimizing_the_model.mp4 93.1 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 86.9 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/11-demonstration_building_basic_cnn_model_with_new_parameters.mp4 82.0 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/13-single_layer_perceptron_decision_boundary.mp4 80.9 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 78.3 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/08-demonstration_handwritten_digits_classification_designing_the_model.mp4 76.8 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/10-demonstration_adding_more_layers.mp4 65.4 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/06-demonstration_rnn_building_the_model.mp4 65.4 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/05-demonstration_rnn_dataset_preparation.mp4 65.1 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/08-demonstration_next_word_prediction_layers.mp4 61.8 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/06-demonstration_model_compilation_preparing_the_dataset.mp4 58.2 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 56.2 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/07-demonstration_designing_the_model.mp4 55.4 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/07-demonstration_next_word_prediction_processing_the_corpus.mp4 52.6 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/07-demonstration_building_and_compiling_model.mp4 48.5 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/08-demonstration_from_rmsprop_to_adam.mp4 47.4 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/12-single_layer_perceptron_define_sigmoid_function.mp4 46.1 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/03-neural_networks.mp4 44.2 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/06-demonstration_load_and_preprocess_the_data.mp4 44.1 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/07-demonstration_handwritten_digits_classification_data_preprocessing.mp4 43.8 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/05-demonstration_building_a_simple_neural_network.mp4 42.9 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/06-demonstration_understanding_how_backpropagation_has_worked.mp4 42.4 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/08-demonstration_building_the_cnn_model.mp4 39.8 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/12-demonstration_pre_trained_model.mp4 39.2 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 38.8 MB
  • 01-Deep_Learning_Components/04-Module_Wrap_Up_And_Assessment/01-summary_of_deep_learning_components.mp4 38.1 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/01-machine_learning_vs_deep_learning.mp4 35.9 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/01-improving_a_model.mp4 34.5 MB
  • 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 34.5 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/05-fast_regional_cnn.mp4 33.7 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/04-convolutional_layer.mp4 33.5 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/05-working_of_convolutional_layer.mp4 33.5 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/03-using_adam_optimizer.mp4 33.5 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/03-visual_cortex_and_cnn.mp4 33.1 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/02-introduction_to_rcnn.mp4 33.0 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/07-perceptron.mp4 32.4 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/01-classification_and_object_detection.mp4 31.3 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/08-learning_rate.mp4 30.7 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/04-pre_trained_model.mp4 30.5 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/03-rnn_architecture_workflow.mp4 30.3 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/04-implementing_rnn.mp4 30.3 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/01-basics_of_lstm.mp4 29.7 MB
  • 01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/02-course_introduction.mp4 29.3 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/01-limitations_of_mlp.mp4 29.3 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/05-model_compilation_with_popular_frameworks.mp4 28.7 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/02-advent_of_faster_r_cnn.mp4 26.5 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/01-fast_rcnn_limitations.mp4 26.1 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/11-importance_of_epoch.mp4 26.0 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/04-artificial_neural_network_ann.mp4 25.6 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/02-lstm_structure.mp4 25.4 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/10-activation_function_and_its_types.mp4 24.6 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 24.5 MB
  • 04-Course_Wrap_Up_And_Assessment/01-course_summary_for_practical_deep_learning_with_python.mp4 24.5 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/05-importance_of_lstm_architecture.mp4 24.2 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/02-rnn_architecture.mp4 23.7 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/04-Module_Wrap_Up_And_Assessment/02-summary_of_faster_rcnn.mp4 23.6 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/02-model_optimization.mp4 22.9 MB
  • 01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/03-environment_configuration.mp4 22.9 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/02-mlp_limitations_resolving_the_issue_with_cnn.mp4 22.6 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/09-demonstration_model_accuracy.mp4 22.5 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/03-forget_gate_and_input_gate.mp4 21.9 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/06-forward_propagation.mp4 21.6 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/01-rnn_fundamentals.mp4 21.5 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/03-tensorflow_hub.mp4 21.3 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/02-what_is_deep_learning.mp4 21.3 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/06-types_of_lstm.mp4 20.1 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/09-what_is_activation_function.mp4 18.7 MB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/05-ann_types_and_applications.mp4 18.6 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/04-backpropagation.mp4 17.8 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/04-model_compilation.mp4 15.1 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/04-output_gate.mp4 14.8 MB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/04-Module_Wrap_Up_And_Assessment/01-summary_of_cnn_in_deep_learning.mp4 14.0 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 13.1 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/02-multi_layered_perceptron.mp4 12.6 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/01-limitations_of_single_layered_perceptron.mp4 11.6 MB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/03-what_is_backpropagation.mp4 10.8 MB
  • Resources/01-Module_3_Datasets/next_word_model.keras 10.2 MB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/09-model_optimizers_beyond_adam_instructions.html 89.4 kB
  • Resources/02-Module_2_Datasets/resources.html 67.3 kB
  • 04-Course_Wrap_Up_And_Assessment/02-practice_project_mnist_fashion_dataset_analysis_instructions.html 65.5 kB
  • 01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/10-hebbian_learning_algorithm_instructions.html 27.9 kB
  • 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 20.1 kB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/10-attention_based_lstm_long_short_term_memory_instructions.html 7.6 kB
  • 01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/01-welcome_to_practical_deep_learning_with_python_instructions.html 7.4 kB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/06-faster_r_cnn_architecture_instructions.html 6.1 kB
  • 01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/04-system_requirements_and_pre_requisite_for_studying_deep_learning_instructions.html 4.6 kB
  • 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 4.4 kB
  • 03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/11-capsule_networks_in_deep_learning_instructions.html 4.3 kB
  • 01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/14-learning_rate_in_deep_learning_instructions.html 4.0 kB
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/13-why_convolutions_are_important_instructions.html 2.1 kB
  • Resources/01-Module_3_Datasets/history.p 436 Bytes
  • 02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/01. Support - Onehack.Us.txt 94 Bytes
  • Support - Onehack.Us.txt 94 Bytes

随机展示

相关说明

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！