Coursera | Practical Deep Learning With Python 2025

To download this torrent, you need a BitTorrent client: Vuze or BTGuard

< حجم الخط = 2pt > تحميل هذا السيل
Download using Magnet Link

الصحة:

بذور: 131
leechers: 66
إكمال: 974
آخر فحص: 12-03-2025 19:52:56

< لون الخط أبيض = > نقاط سمعة رافع : 17748

Thanks By

Write a Review for the Uploader:	245	Say Thanks with one good review:

Share on Facebook

Details

اسم:	Coursera \| Practical Deep Learning With Python 2025
الوصف: Coursera - Practical Deep Learning With Python 2025 Course details 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 ... What you'll learn - Understand the core components of deep learning models and their role in AI. - Apply CNN, R-CNN, and Faster R-CNN for object detection tasks. - Implement RNNs and LSTMs for sequential data processing. - Optimize and evaluate deep learning models for improved performance. There are 4 modules in this course 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. Experience in building machine learning models, along with knowledge of statistics and proficiency in Python programming, is recommended for this course. Embark on this educational journey to enhance your expertise in deep learning and elevate your capabilities in building intelligent systems for the future of artificial intelligence. General Details: Duration: 6h 10m Updated: 03/2025 Language: English Source: https://www.coursera.org/learn/practical-deep-learning-with-python Instructor: https://www.edureka.co/ MP4 \| Video: AVC, 1920x1080p \| Audio: AAC, 44.100 KHz, 2 Ch
يوتيوب فيديو:
الفئة:	Tutorials
اللغة:	English
إجمالي حجم:	2.66 GB
تجزئة المعلومات:	C7BB387E940A369D54E1C25A892B00661CB93B3B
وأضاف بها:	Prom3th3uS
تاريخ الإضافة:	2025-03-12 04:56:51
سيل مركز:	Torrent Verified by Prom3th3uS on 11th March, 2025

تصنيفات:

Not Yet Rated (Log in to rate it)

Tracker:
udp://tracker.torrent.eu.org:451/announce

هذا السيل كما قد تتبع النسخ الاحتياطي

URL	آلات	leechers	إكمال
udp://tracker.torrent.eu.org:451/announce	25	8	169
udp://open.demonii.com:1337/announce	1	19	17
udp://tracker.tiny-vps.com:6969/announce	8	2	202
udp://exodus.desync.com:6969/announce	10	2	44
udp://explodie.org:6969/announce	3	1	0
udp://tracker.opentrackr.org:1337/announce	39	12	303
udp://open.stealth.si:80/announce	23	10	162
udp://tracker.dler.org:6969/announce	2	0	7
udp://opentracker.io:6969/announce	5	2	25
udp://tracker.0x7c0.com:6969/announce	4	3	27
udp://evan.im:6969/announce	2	2	0
udp://p4p.arenabg.com:1337/announce	6	2	0
udp://bandito.byterunner.io:6969/announce	3	3	18

ملف قائمة:

ملف	حجم
01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/01-welcome_to_practical_deep_learning_with_python_instructions.html	7.21 kB
01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/02-course_introduction.mp4	27.98 MB
01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/03-environment_configuration.mp4	21.82 MB
01-Deep_Learning_Components/01-Environment_Set_Up_And_Configuration/04-system_requirements_and_pre_requisite_for_studying_deep_learning_instructions.html	4.51 kB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/01-machine_learning_vs_deep_learning.mp4	34.27 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/02-what_is_deep_learning.mp4	20.31 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/03-neural_networks.mp4	42.16 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/04-artificial_neural_network_ann.mp4	24.40 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/05-ann_types_and_applications.mp4	17.78 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/06-forward_propagation.mp4	20.61 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/07-perceptron.mp4	30.93 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/08-learning_rate.mp4	29.25 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/09-what_is_activation_function.mp4	17.83 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/10-activation_function_and_its_types.mp4	23.41 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/11-importance_of_epoch.mp4	24.78 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/12-single_layer_perceptron_define_sigmoid_function.mp4	44.01 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/13-single_layer_perceptron_decision_boundary.mp4	77.15 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/14-learning_rate_in_deep_learning_instructions.html	3.86 kB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/01-limitations_of_single_layered_perceptron.mp4	11.05 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/02-multi_layered_perceptron.mp4	12.04 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/03-what_is_backpropagation.mp4	10.26 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/04-backpropagation.mp4	17.00 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/05-demonstration_building_a_simple_neural_network.mp4	40.88 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/06-demonstration_understanding_how_backpropagation_has_worked.mp4	40.45 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/07-demonstration_handwritten_digits_classification_data_preprocessing.mp4	41.79 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/08-demonstration_handwritten_digits_classification_designing_the_model.mp4	73.22 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/09-demonstration_handwritten_digits_classification_optimizing_the_model.mp4	88.77 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/10-hebbian_learning_algorithm_instructions.html	27.28 kB
01-Deep_Learning_Components/04-Module_Wrap_Up_And_Assessment/01-summary_of_deep_learning_components.mp4	36.33 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/01-limitations_of_mlp.mp4	27.91 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/01. Support - Onehack.Us.txt	94.00 B
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/02-mlp_limitations_resolving_the_issue_with_cnn.mp4	21.51 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/03-visual_cortex_and_cnn.mp4	31.61 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/04-convolutional_layer.mp4	31.99 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/05-working_of_convolutional_layer.mp4	31.99 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/06-demonstration_load_and_preprocess_the_data.mp4	42.04 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/07-demonstration_designing_the_model.mp4	52.84 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/08-demonstration_building_the_cnn_model.mp4	37.97 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/09-demonstration_model_accuracy.mp4	21.46 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/10-demonstration_adding_more_layers.mp4	62.39 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/11-demonstration_building_basic_cnn_model_with_new_parameters.mp4	78.21 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/12-demonstration_pre_trained_model.mp4	37.38 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/13-why_convolutions_are_important_instructions.html	2.08 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	29.81 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/02-introduction_to_rcnn.mp4	31.51 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	12.46 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/04-pre_trained_model.mp4	29.04 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/05-fast_regional_cnn.mp4	32.10 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	37.00 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	53.63 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	23.40 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	4.26 kB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/01-fast_rcnn_limitations.mp4	24.90 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/02-advent_of_faster_r_cnn.mp4	25.24 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/03-tensorflow_hub.mp4	20.32 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	74.66 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	82.91 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/06-faster_r_cnn_architecture_instructions.html	5.92 kB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/04-Module_Wrap_Up_And_Assessment/01-summary_of_cnn_in_deep_learning.mp4	13.32 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/04-Module_Wrap_Up_And_Assessment/02-summary_of_faster_rcnn.mp4	22.48 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/01-rnn_fundamentals.mp4	20.50 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/02-rnn_architecture.mp4	22.59 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/03-rnn_architecture_workflow.mp4	28.92 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/04-implementing_rnn.mp4	28.87 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/05-demonstration_rnn_dataset_preparation.mp4	62.04 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/06-demonstration_rnn_building_the_model.mp4	62.38 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	19.64 kB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/01-basics_of_lstm.mp4	28.36 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/02-lstm_structure.mp4	24.24 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/03-forget_gate_and_input_gate.mp4	20.87 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/04-output_gate.mp4	14.09 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/05-importance_of_lstm_architecture.mp4	23.04 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/06-types_of_lstm.mp4	19.16 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/07-demonstration_next_word_prediction_processing_the_corpus.mp4	50.16 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/08-demonstration_next_word_prediction_layers.mp4	58.93 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/09-demonstration_next_word_prediction_model_compilation_and_prediction.mp4	96.56 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/10-attention_based_lstm_long_short_term_memory_instructions.html	7.41 kB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/11-capsule_networks_in_deep_learning_instructions.html	4.17 kB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/01-improving_a_model.mp4	32.93 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/02-model_optimization.mp4	21.84 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/03-using_adam_optimizer.mp4	31.96 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/04-model_compilation.mp4	14.37 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/05-model_compilation_with_popular_frameworks.mp4	27.34 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/06-demonstration_model_compilation_preparing_the_dataset.mp4	55.53 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/07-demonstration_building_and_compiling_model.mp4	46.26 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/08-demonstration_from_rmsprop_to_adam.mp4	45.17 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/09-model_optimizers_beyond_adam_instructions.html	87.35 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	32.88 MB
04-Course_Wrap_Up_And_Assessment/01-course_summary_for_practical_deep_learning_with_python.mp4	23.39 MB
04-Course_Wrap_Up_And_Assessment/02-practice_project_mnist_fashion_dataset_analysis_instructions.html	64.00 kB
Resources/01-Module_3_Datasets/history.p	436.00 B
Resources/01-Module_3_Datasets/next_word_model.keras	9.76 MB
Resources/02-Module_2_Datasets/resources.html	65.68 kB
Support - Onehack.Us.txt	94.00 B

Comments
لا توجد تعليقات نشرت ما زال

أفلام

تلفزيون

البرمجيات/تطبيقات

الموسيقى

الألعاب

كتب

انيمي

تطبيقات الجوال/ألعاب

فيديو

صور

تلفزيون/فيلم حزم

Coursera | Practical Deep Learning With Python 2025