English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 375 Lessons (59h 0m) | 5.91 GB
Become a Machine Learning expert. Master the fundamentals of deep learning and break into AI. Recently updated with cutting-edge techniques!
What you’ll learn
- Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications
- Train test sets, analyze variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in TensorFlow
- Build a CNN and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data
- Build and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering
Skills you’ll gain
- Recurrent Neural Network
- Tensorflow
- Convolutional Neural Network
- Artificial Neural Network
- Transformers
The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.
In this Specialization, you will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. Get ready to master theoretical concepts and their industry applications using Python and TensorFlow and tackle real-world cases such as speech recognition, music synthesis, chatbots, machine translation, natural language processing, and more.
AI is transforming many industries. The Deep Learning Specialization provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career. Along the way, you will also get career advice from deep learning experts from industry and academia.
Applied Learning Project
By the end you’ll be able to
- Build and train deep neural networks, implement vectorized neural networks, identify architecture parameters, and apply DL to your applications
- Use best practices to train and develop test sets and analyze bias/variance for building DL applications, use standard NN techniques, apply optimization algorithms, and implement a neural network in TensorFlow
- Use strategies for reducing errors in ML systems, understand complex ML settings, and apply end-to-end, transfer, and multi-task learning
- Build a Convolutional Neural Network, apply it to visual detection and recognition tasks, use neural style transfer to generate art, and apply these algorithms to image, video, and other 2D/3D data
- Build and train Recurrent Neural Networks and its variants (GRUs, LSTMs), apply RNNs to character-level language modeling, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformers to perform Named Entity Recognition and Question Answering
Table of Contents
convolutional-neural-networks
foundations-of-convolutional-neural-networks
convolutional-neural-networks
1 computer-vision
2 computer-vision_3307320-Computer_Vision-extended-description-mixed
3 edge-detection-example
4 edge-detection-example_3307344-Edge_Detection_Example-extended-description-mixed
5 more-edge-detection
6 more-edge-detection_3307355-More_Edge_Detection-extended-description-mixed
7 padding
8 padding_3307360-Padding-extended-description-mixed
9 join-the-deeplearning-ai-forum-to-ask-questions-get-support-or-share-amazing_instructions
10 strided-convolutions
11 strided-convolutions_3307364-Strided_Convolutions-extended-description-mixed
12 convolutions-over-volume
13 convolutions-over-volume_3307341-Convolutions_Over_Volume-extended-description-mixed
14 one-layer-of-a-convolutional-network
15 one-layer-of-a-convolutional-network_3307324-One_Layer_of_a_Convolutional_Network-extended-description-mixed
16 clarifications-about-upcoming-simple-convolutional-network-example-video_instructions
17 simple-convolutional-network-example
18 simple-convolutional-network-example_3307363-Simple_Convolutional_Network_Example-extended-description-mixed
19 pooling-layers
20 pooling-layers_3307361-Pooling_Layers-extended-description-mixed
21 clarifications-about-upcoming-cnn-example-video_instructions
22 cnn-example
23 cnn-example_3307337-CNN_Example-extended-description-mixed
24 clarifications-about-upcoming-why-convolutions_instructions
25 why-convolutions
26 why-convolutions_3307372-Why_Convolutions_-extended-description-mixed
lecture-notes-optional
27 lecture-notes-w1_instructions
programming-assignments
28 optional-downloading-your-notebook-downloading-your-workspace-and-refreshing_instructions
heroes-of-deep-learning-optional
29 yann-lecun-interview
30 yann-lecun-interview_3307380-Yann_LeCun_Interview-extended-description-mixed
deep-convolutional-models-case-studies
case-studies
31 why-look-at-case-studies
32 why-look-at-case-studies_3307378-Why_look_at_case_studies_-extended-description-mixed
33 classic-networks
34 classic-networks_3307318-Classic_Networks-extended-description-mixed
35 resnets
36 resnets_3307326-ResNets-extended-description-mixed
37 why-resnets-work
38 why-resnets-work_3307379-Why_ResNets_Work-extended-description-mixed
39 networks-in-networks-and-1×1-convolutions
40 networks-in-networks-and-1×1-convolutions_3307322-Networks_in_Networks_and_1x1_Convolutions-extended-description-mixed
41 clarifications-about-upcoming-inception-network-motivation-video_instructions
42 inception-network-motivation
43 inception-network-motivation_3307345-Inception_Network_Motivation-extended-description-mixed_1
44 inception-network
45 inception-network_3307346-Inception_Network-extended-description-mixed
46 mobilenet
47 mobilenet-architecture
48 efficientnet
practical-advice-for-using-convnets
49 using-open-source-implementation
50 using-open-source-implementation_3307368-Using_Open-Source_Implementation-extended-description-mixed
51 transfer-learning
52 transfer-learning_3307366-Transfer_Learning-extended-description-mixed
53 data-augmentation
54 data-augmentation_3307343-Data_Augmentation-extended-description-mixed
55 state-of-computer-vision
56 state-of-computer-vision_3307328-State_of_Computer_Vision-extended-description-mixed
lecture-notes-optional
57 lecture-notes-w2_instructions
programming-assignments
58 note-on-the-upcoming-programming-assignment-residual-networks_instructions
object-detection
detection-algorithms
59 object-localization
60 object-localization_3307358-Object_Localization-extended-description-mixed
61 landmark-detection
62 landmark-detection_3307354-Landmark_Detection-extended-description-mixed
63 object-detection
64 object-detection_3307357-Object_Detection-extended-description-mixed
65 clarifications-about-upcoming-convolutional-implementation-of-sliding-windows_instructions
66 convolutional-implementation-of-sliding-windows
67 convolutional-implementation-of-sliding-windows_3307340-Convolutional_Implementation_of_Sliding_Windows-extended-description-mixed
68 bounding-box-predictions
69 bounding-box-predictions_3307336-Bounding_Box_Predictions-extended-description-mixed
70 intersection-over-union
71 intersection-over-union_3307353-Intersection_Over_Union-extended-description-mixed
72 non-max-suppression
73 non-max-suppression_3307356-Non-max_Suppression-extended-description-mixed
74 anchor-boxes
75 anchor-boxes_3307335-Anchor_Boxes-extended-description-mixed
76 clarifications-about-upcoming-yolo-algorithm-video_instructions
77 yolo-algorithm
78 yolo-algorithm_3307381-YOLO_Algorithm-extended-description-mixed
79 region-proposals-optional
80 region-proposals-optional_3307330-_Optional__Region_Proposals-extended-description-mixed
81 semantic-segmentation-with-u-net
82 transpose-convolutions
83 u-net-architecture-intuition
84 u-net-architecture
lecture-notes-optional
85 lecture-notes-w3_instructions
programming-assignments
86 clear-output-before-submitting-for-u-net-assignment_instructions
special-applications-face-recognition-neural-style-transfer
face-recognition
87 what-is-face-recognition
88 what-is-face-recognition_3307370-What_is_face_recognition_-extended-description-mixed
89 one-shot-learning
90 one-shot-learning_3307359-One_Shot_Learning-extended-description-mixed
91 siamese-network
92 siamese-network_3307362-Siamese_Network-extended-description-mixed
93 triplet-loss
94 triplet-loss_3307367-Triplet_Loss-extended-description-mixed
95 clarifications-about-upcoming-face-verification-and-binary-classification-video_instructions
96 face-verification-and-binary-classification
97 face-verification-and-binary-classification_3307321-Face_Verification_and_Binary_Classification-extended-description-mixed
neural-style-transfer
98 what-is-neural-style-transfer
99 what-is-neural-style-transfer_3307371-What_is_neural_style_transfer_-extended-description-mixed
100 what-are-deep-convnets-learning
101 what-are-deep-convnets-learning_3307369-What_are_deep_ConvNets_learning_-extended-description-mixed
102 cost-function
103 cost-function_3307342-Cost_Function-extended-description-mixed
104 content-cost-function
105 content-cost-function_3307339-Content_Cost_Function-extended-description-mixed
106 clarifications-about-upcoming-style-cost-function-video_instructions
107 style-cost-function
108 style-cost-function_3307365-Style_Cost_Function-extended-description-mixed
109 d-and-3d-generalizations
110 d-and-3d-generalizations_3307332-1D_and_3D_Generalizations-extended-description-mixed
lecture-notes-optional
111 lecture-notes-w4_instructions
end-of-access-to-lab-notebooks
112 important-reminder-about-end-of-access-to-lab-notebooks_instructions
references-acknowledgments
113 references_instructions
114 acknowledgments_instructions
Resources
course-acknowledgments
115 resources
deep-neural-network
practical-aspects-of-deep-learning
setting-up-your-machine-learning-application
116 train-dev-test-sets
117 train-dev-test-sets_3307250-Train___Dev___Test_sets-extended-description-mixed
118 bias-variance
119 bias-variance_3307225-Bias___Variance-extended-description-mixed
120 basic-recipe-for-machine-learning
121 basic-recipe-for-machine-learning_3307223-Basic_Recipe_for_Machine_Learning-extended-description-mixed
connect-with-your-mentors-and-fellow-learners-on-our-forum
122 join-the-deeplearning-ai-forum-to-ask-questions-get-support-or-share-amazing_instructions
regularizing-your-neural-network
123 clarification-about-upcoming-regularization-video_instructions
124 regularization
125 regularization_3307245-Regularization-extended-description-mixed
126 why-regularization-reduces-overfitting
127 why-regularization-reduces-overfitting_3307259-Why_regularization_reduces_overfitting_-extended-description-mixed
128 dropout-regularization
129 dropout-regularization_3307228-Dropout_Regularization-extended-description-mixed
130 clarification-about-upcoming-understanding-dropout-video_instructions
131 understanding-dropout
132 understanding-dropout_3307253-Understanding_Dropout-extended-description-mixed
133 other-regularization-methods
134 other-regularization-methods_3307241-Other_regularization_methods-extended-description-mixed
setting-up-your-optimization-problem
135 normalizing-inputs
136 normalizing-inputs_3307239-Normalizing_inputs-extended-description-mixed
137 vanishing-exploding-gradients
138 vanishing-exploding-gradients_3307257-Vanishing___Exploding_gradients-extended-description-mixed
139 weight-initialization-for-deep-networks
140 weight-initialization-for-deep-networks_3307221-Weight_Initialization_for_Deep_Networks-extended-description-mixed
141 numerical-approximation-of-gradients
142 numerical-approximation-of-gradients_3307240-Numerical_approximation_of_gradients-extended-description-mixed
143 gradient-checking
144 gradient-checking_3307233-Gradient_checking-extended-description-mixed
145 gradient-checking-implementation-notes
146 gradient-checking-implementation-notes_3307231-Gradient_Checking_Implementation_Notes-extended-description-mixed
lecture-notes-optional
147 lecture-notes-w1_instructions
programming-assignments
148 optional-downloading-your-notebook-downloading-your-workspace-and-refreshing_instructions
heroes-of-deep-learning-optional
149 yoshua-bengio-interview
150 yoshua-bengio-interview_3307260-Yoshua_Bengio_interview-extended-description-mixed
optimization-algorithms
optimization-algorithms
151 mini-batch-gradient-descent
152 mini-batch-gradient-descent_3307220-Mini-batch_gradient_descent-extended-description-mixed
153 understanding-mini-batch-gradient-descent
154 understanding-mini-batch-gradient-descent_3307255-Understanding_mini-batch_gradient_descent-extended-description-mixed
155 exponentially-weighted-averages
156 exponentially-weighted-averages_3307229-Exponentially_weighted_averages-extended-description-mixed
157 understanding-exponentially-weighted-averages
158 understanding-exponentially-weighted-averages_3307254-Understanding_exponentially_weighted_averages-extended-description-mixed
159 bias-correction-in-exponentially-weighted-averages
160 bias-correction-in-exponentially-weighted-averages_3307226-Bias_correction_in_exponentially_weighted_averages-extended-description-mixed
161 gradient-descent-with-momentum
162 gradient-descent-with-momentum_3307234-Gradient_descent_with_momentum-extended-description-mixed
163 rmsprop
164 rmsprop_3307246-RMSprop-extended-description-mixed
165 clarification-about-upcoming-adam-optimization-video_instructions
166 adam-optimization-algorithm
167 adam-optimization-algorithm_3307222-Adam_optimization_algorithm-extended-description-mixed
168 clarification-about-learning-rate-decay-video_instructions
169 learning-rate-decay
170 learning-rate-decay_3307237-Learning_rate_decay-extended-description-mixed
171 the-problem-of-local-optima
172 the-problem-of-local-optima_3307249-The_problem_of_local_optima-extended-description-mixed
lecture-notes-optional
173 lecture-notes-w2_instructions
heroes-of-deep-learning-optional
174 yuanqing-lin-interview
175 yuanqing-lin-interview_3307261-Yuanqing_Lin_interview-extended-description-mixed
hyperparameter-tuning-batch-normalization-and-programming-frameworks
hyperparameter-tuning
176 tuning-process
177 tuning-process_3307252-Tuning_process-extended-description-mixed
178 using-an-appropriate-scale-to-pick-hyperparameters
179 using-an-appropriate-scale-to-pick-hyperparameters_3307256-Using_an_appropriate_scale_to_pick_hyperparameters-extended-description-mixed
180 hyperparameters-tuning-in-practice-pandas-vs-caviar
181 hyperparameters-tuning-in-practice-pandas-vs-caviar_3307235-Hyperparameters_tuning_in_practice_Pandas_vs_Caviar-extended-description-mixed
batch-normalization
182 clarification-about-upcoming-normalizing-activations-in-a-network-video_instructions
183 normalizing-activations-in-a-network
184 normalizing-activations-in-a-network_3307238-Normalizing_activations_in_a_network-extended-description-mixed
185 fitting-batch-norm-into-a-neural-network
186 fitting-batch-norm-into-a-neural-network_3307230-Fitting_Batch_Norm_into_a_neural_network-extended-description-mixed
187 why-does-batch-norm-work
188 why-does-batch-norm-work_3307258-Why_does_Batch_Norm_work_-extended-description-mixed
189 batch-norm-at-test-time
190 batch-norm-at-test-time_3307224-Batch_Norm_at_test_time-extended-description-mixed
multi-class-classification
191 clarifications-about-upcoming-softmax-video_instructions
192 softmax-regression
193 softmax-regression_3307247-Softmax_Regression-extended-description-mixed
194 training-a-softmax-classifier
195 training-a-softmax-classifier_3307251-Training_a_softmax_classifier-extended-description-mixed
introduction-to-programming-frameworks
196 deep-learning-frameworks
197 deep-learning-frameworks_3307227-Deep_learning_frameworks-extended-description-mixed
198 tensorflow
199 tensorflow_3307248-TensorFlow-extended-description-mixed
200 optional-learn-about-gradient-tape-and-more_instructions
lecture-notes-optional
201 lecture-notes-w3_instructions
end-of-access-to-lab-notebooks
202 important-reminder-about-end-of-access-to-lab-notebooks_instructions
references-acknowledgments
203 references_instructions
204 acknowledgments_instructions
machine-learning-projects
ml-strategy
introduction-to-ml-strategy
205 why-ml-strategy
206 why-ml-strategy_3307295-Why_ML_Strategy-extended-description-mixed
207 orthogonalization
208 orthogonalization_3307274-Orthogonalization-extended-description-mixed
connect-with-your-mentors-and-fellow-learners-on-our-forum
209 join-the-deeplearning-ai-forum-to-ask-questions-get-support-or-share-amazing_instructions
setting-up-your-goal
210 single-number-evaluation-metric
211 single-number-evaluation-metric_3307277-Single_number_evaluation_metric-extended-description-mixed
212 satisficing-and-optimizing-metric
213 satisficing-and-optimizing-metric_3307276-Satisficing_and_Optimizing_metric-extended-description-mixed
214 train-dev-test-distributions
215 train-dev-test-distributions_3307279-Train_dev_test_distributions-extended-description-mixed
216 size-of-the-dev-and-test-sets
217 size-of-the-dev-and-test-sets_3307265-Size_of_the_dev_and_test_sets-extended-description-mixed
218 when-to-change-dev-test-sets-and-metrics
219 when-to-change-dev-test-sets-and-metrics_3307290-When_to_change_dev_test_sets_and_metrics-extended-description-mixed
comparing-to-human-level-performance
220 why-human-level-performance
221 why-human-level-performance_3307292-Why_human-level_performance_-extended-description-mixed
222 avoidable-bias
223 avoidable-bias_3307268-Avoidable_bias-extended-description-mixed
224 understanding-human-level-performance
225 understanding-human-level-performance_3307282-Understanding_human-level_performance-extended-description-mixed
226 surpassing-human-level-performance
227 surpassing-human-level-performance_3307278-Surpassing_human-level_performance-extended-description-mixed
228 improving-your-model-performance
229 improving-your-model-performance_3307264-Improving_your_model_performance-extended-description-mixed
lecture-notes-optional
230 lecture-notes-w1_instructions
machine-learning-flight-simulator-quiz
heroes-of-deep-learning-optional
231 andrej-karpathy-interview
232 andrej-karpathy-interview_3307267-Andrej_Karpathy_interview-extended-description-mixed
ml-strategy
error-analysis
233 carrying-out-error-analysis
234 carrying-out-error-analysis_3307271-Carrying_out_error_analysis-extended-description-mixed
235 cleaning-up-incorrectly-labeled-data
236 cleaning-up-incorrectly-labeled-data_3307272-Cleaning_up_incorrectly_labeled_data-extended-description-mixed
237 build-your-first-system-quickly-then-iterate
238 build-your-first-system-quickly-then-iterate_3307270-Build_your_first_system_quickly__then_iterate-extended-description-mixed
mismatched-training-and-dev-test-set
239 training-and-testing-on-different-distributions
240 training-and-testing-on-different-distributions_3307280-Training_and_testing_on_different_distributions-extended-description-mixed
241 bias-and-variance-with-mismatched-data-distributions
242 bias-and-variance-with-mismatched-data-distributions_3307269-Bias_and_Variance_with_mismatched_data_distributions-extended-description-mixed
243 addressing-data-mismatch
244 addressing-data-mismatch_3307266-Addressing_data_mismatch-extended-description-mixed
learning-from-multiple-tasks
245 transfer-learning
246 transfer-learning_3307281-Transfer_learning-extended-description-mixed
247 multi-task-learning
248 multi-task-learning_3307273-Multi-task_learning-extended-description-mixed
end-to-end-deep-learning
249 what-is-end-to-end-deep-learning
250 what-is-end-to-end-deep-learning_3307284-What_is_end-to-end_deep_learning_-extended-description-mixed
251 whether-to-use-end-to-end-deep-learning
252 whether-to-use-end-to-end-deep-learning_3307291-Whether_to_use_end-to-end_deep_learning-extended-description-mixed
lecture-notes-optional
253 lecture-notes-w2_instructions
heroes-of-deep-learning-optional
254 ruslan-salakhutdinov-interview
255 ruslan-salakhutdinov-interview_3307275-Ruslan_Salakhutdinov_interview-extended-description-mixed
acknowledgments
256 acknowledgments_instructions
neural-networks-deep-learning
introduction-to-deep-learning
welcome-to-the-deep-learning-specialization
257 welcome
258 welcome_3287059-Welcome-extended-description-mixed_1
introduction-to-deep-learning
259 what-is-a-neural-network
260 what-is-a-neural-network_3307190-What_is_a_neural_network_-extended-description-mixed
261 supervised-learning-with-neural-networks
262 supervised-learning-with-neural-networks_3307180-Supervised_Learning_with_Neural_Networks-extended-description-mixed
263 why-is-deep-learning-taking-off
264 why-is-deep-learning-taking-off_3307192-Why_is_Deep_Learning_taking_off_-extended-description-mixed
265 about-this-course
266 join-the-deeplearning-ai-forum-to-ask-questions-get-support-or-share-amazing_instructions
267 frequently-asked-questions_instructions
lecture-notes-optional
268 lecture-notes-w1_instructions
heroes-of-deep-learning-optional
269 geoffrey-hinton-interview
270 geoffrey-hinton-interview_3307169-Geoffrey_Hinton_interview-extended-description-mixed
neural-networks-basics
logistic-regression-as-a-neural-network
271 binary-classification
272 binary-classification_3307141-Binary_Classification-extended-description-mixed
273 logistic-regression
274 logistic-regression_3307132-Logistic_Regression-extended-description-mixed
275 logistic-regression-cost-function
276 logistic-regression-cost-function_3307173-Logistic_Regression_Cost_Function-extended-description-mixed
277 gradient-descent
278 gradient-descent_3307171-Gradient_Descent-extended-description-mixed
279 derivatives
280 derivatives_3307124-Derivatives-extended-description-mixed
281 more-derivative-examples
282 more-derivative-examples_3307133-More_Derivative_Examples-extended-description-mixed
283 computation-graph
284 computation-graph_3307143-Computation_graph-extended-description-mixed
285 derivatives-with-a-computation-graph
286 derivatives-with-a-computation-graph_3307164-Derivatives_with_a_Computation_Graph-extended-description-mixed
287 logistic-regression-gradient-descent
288 logistic-regression-gradient-descent_3307174-Logistic_Regression_Gradient_Descent-extended-description-mixed
289 gradient-descent-on-m-examples
290 gradient-descent-on-m-examples_3307131-Gradient_Descent_on_m_Examples-extended-description-mixed
291 derivation-of-dl-dz-optional_instructions
python-and-vectorization
292 vectorization
293 vectorization_3307184-Vectorization-extended-description-mixed
294 more-vectorization-examples
295 more-vectorization-examples_3307175-More_Vectorization_Examples-extended-description-mixed
296 vectorizing-logistic-regression
297 vectorizing-logistic-regression_3307188-Vectorizing_Logistic_Regression-extended-description-mixed
298 vectorizing-logistic-regressions-gradient-output
299 vectorizing-logistic-regressions-gradient-output_3307189-Vectorizing_Logistic_Regression_s_Gradient_Output-extended-description-mixed
300 broadcasting-in-python
301 broadcasting-in-python_3307142-Broadcasting_in_Python-extended-description-mixed
302 a-note-on-python-numpy-vectors
303 a-note-on-python-numpy-vectors_3307138-A_note_on_python_numpy_vectors-extended-description-mixed
304 quick-tour-of-jupyter-ipython-notebooks
305 quick-tour-of-jupyter-ipython-notebooks_3307178-Quick_tour_of_Jupyter_iPython_Notebooks-extended-description-mixed
306 explanation-of-logistic-regression-cost-function-optional
307 explanation-of-logistic-regression-cost-function-optional_3307166-Explanation_of_logistic_regression_cost_function__optional_-extended-description-mixed
lecture-notes-optional
308 lecture-notes-w2_instructions
programming-assignments
309 deep-learning-honor-code_instructions
310 programming-assignment-faq_instructions
311 optional-downloading-your-notebook-downloading-your-workspace-and-refreshing_instructions
heroes-of-deep-learning-optional
312 pieter-abbeel-interview
313 pieter-abbeel-interview_3307177-Pieter_Abbeel_interview-extended-description-mixed
shallow-neural-networks
shallow-neural-network
314 neural-networks-overview
315 neural-networks-overview_3307135-Neural_Networks_Overview-extended-description-mixed
316 neural-network-representation
317 neural-network-representation_3307134-Neural_Network_Representation-extended-description-mixed
318 computing-a-neural-networks-output
319 computing-a-neural-networks-output_3307122-Computing_a_Neural_Network_s_Output-extended-description-mixed
320 vectorizing-across-multiple-examples
321 vectorizing-across-multiple-examples_3307185-Vectorizing_across_multiple_examples-extended-description-mixed
322 explanation-for-vectorized-implementation
323 explanation-for-vectorized-implementation_3307165-Explanation_for_Vectorized_Implementation-extended-description-mixed
324 activation-functions
325 activation-functions_3307140-Activation_functions-extended-description-mixed
326 why-do-you-need-non-linear-activation-functions
327 why-do-you-need-non-linear-activation-functions_3307137-Why_do_you_need_non-linear_activation_functions_-extended-description-mixed
328 derivatives-of-activation-functions
329 derivatives-of-activation-functions_3307123-Derivatives_of_activation_functions-extended-description-mixed
330 gradient-descent-for-neural-networks
331 gradient-descent-for-neural-networks_3307127-Gradient_descent_for_Neural_Networks-extended-description-mixed
332 backpropagation-intuition-optional
333 backpropagation-intuition-optional_3287057-Backpropagation_intuition__optional_-extended-description-mixed
334 random-initialization
335 random-initialization_3307179-Random_Initialization-extended-description-mixed
lecture-notes-optional
336 lecture-notes-w3_instructions
heroes-of-deep-learning-optional
337 ian-goodfellow-interview
338 ian-goodfellow-interview_3307172-Ian_Goodfellow_interview-extended-description-mixed
deep-neural-networks
deep-neural-network
339 deep-l-layer-neural-network
340 deep-l-layer-neural-network_3307163-Deep_L-layer_neural_network-extended-description-mixed
341 forward-propagation-in-a-deep-network
342 forward-propagation-in-a-deep-network_3307125-Forward_Propagation_in_a_Deep_Network-extended-description-mixed
343 getting-your-matrix-dimensions-right
344 getting-your-matrix-dimensions-right_3307170-Getting_your_matrix_dimensions_right-extended-description-mixed
345 why-deep-representations
346 why-deep-representations_3307191-Why_deep_representations_-extended-description-mixed
347 building-blocks-of-deep-neural-networks
348 building-blocks-of-deep-neural-networks_3307121-Building_blocks_of_deep_neural_networks-extended-description-mixed
349 forward-and-backward-propagation
350 forward-and-backward-propagation_3287058-Forward_and_Backward_Propagation-extended-description-mixed_1
351 optional-reading-feedforward-neural-networks-in-depth_instructions
352 parameters-vs-hyperparameters
353 parameters-vs-hyperparameters_3307176-Parameters_vs_Hyperparameters-extended-description-mixed
354 clarification-for-what-does-this-have-to-do-with-the-brain_instructions
355 what-does-this-have-to-do-with-the-brain
356 what-does-this-have-to-do-with-the-brain_3307136-What_does_this_have_to_do_with_the_brain_-extended-description-mixed
lecture-notes-optional
357 lecture-notes-w4_instructions
end-of-access-to-lab-notebooks
358 important-reminder-about-end-of-access-to-lab-notebooks_instructions
programming-assignments
359 confusing-output-from-the-autograder_instructions
references-acknowledgments
360 references_instructions
361 acknowledgments_instructions
Resources
course-notation-sheet
362 resources
course-acknowledgments
363 resources
nlp-sequence-models
recurrent-neural-networks
recurrent-neural-networks
364 why-sequence-models
365 why-sequence-models_3307390-Why_sequence_models-extended-description-mixed
366 notation
367 notation_3307408-Notation-extended-description-mixed
368 recurrent-neural-network-model
369 recurrent-neural-network-model_3307411-Recurrent_Neural_Network_Model-extended-description-mixed
370 backpropagation-through-time
371 backpropagation-through-time_3307393-Backpropagation_through_time-extended-description-mixed
372 join-the-deeplearning-ai-forum-to-ask-questions-get-support-or-share-amazing_instructions
373 different-types-of-rnns
374 different-types-of-rnns_3307400-Different_types_of_RNNs-extended-description-mixed
375 language-model-and-sequence-generation
376 language-model-and-sequence-generation_3307405-Language_model_and_sequence_generation-extended-description-mixed
377 sampling-novel-sequences
378 sampling-novel-sequences_3307413-Sampling_novel_sequences-extended-description-mixed
379 vanishing-gradients-with-rnns
380 vanishing-gradients-with-rnns_3307417-Vanishing_gradients_with_RNNs-extended-description-mixed
381 clarifications-about-upcoming-gated-recurrent-unit-gru-video_instructions
382 gated-recurrent-unit-gru
383 gated-recurrent-unit-gru_3307403-Gated_Recurrent_Unit__GRU_-extended-description-mixed
384 clarifications-about-upcoming-long-short-term-memory-lstm-video_instructions
385 long-short-term-memory-lstm
386 long-short-term-memory-lstm_3307388-Long_Short_Term_Memory__LSTM_-extended-description-mixed
387 bidirectional-rnn
388 bidirectional-rnn_3307396-Bidirectional_RNN-extended-description-mixed
389 deep-rnns
390 deep-rnns_3307399-Deep_RNNs-extended-description-mixed
lecture-notes-optional
391 lecture-notes-w1_instructions
programming-assignments
392 optional-downloading-your-notebook-downloading-your-workspace-and-refreshing_instructions
natural-language-processing-word-embeddings
introduction-to-word-embeddings
393 word-representation
394 word-representation_3307418-Word_Representation-extended-description-mixed
395 using-word-embeddings
396 using-word-embeddings_3307416-Using_word_embeddings-extended-description-mixed
397 properties-of-word-embeddings
398 properties-of-word-embeddings_3307410-Properties_of_word_embeddings-extended-description-mixed
399 embedding-matrix
400 embedding-matrix_3307401-Embedding_matrix-extended-description-mixed
learning-word-embeddings-word2vec-glove
401 learning-word-embeddings
402 learning-word-embeddings_3307387-Learning_word_embeddings-extended-description-mixed
403 word2vec
404 word2vec_3307419-Word2Vec-extended-description-mixed
405 negative-sampling
406 negative-sampling_3307407-Negative_Sampling-extended-description-mixed
407 clarifications-about-upcoming-glove-word-vectors-video_instructions
408 glove-word-vectors
409 glove-word-vectors_3307404-GloVe_word_vectors-extended-description-mixed
applications-using-word-embeddings
410 sentiment-classification
411 sentiment-classification_3307414-Sentiment_Classification-extended-description-mixed
412 debiasing-word-embeddings
413 debiasing-word-embeddings_3307398-Debiasing_word_embeddings-extended-description-mixed
lecture-notes-optional
414 lecture-notes-w2_instructions
sequence-models-attention-mechanism
various-sequence-to-sequence-architectures
415 basic-models
416 picking-the-most-likely-sentence
417 picking-the-most-likely-sentence_3307409-Picking_the_most_likely_sentence-extended-description-mixed
418 beam-search
419 beam-search_3307395-Beam_Search-extended-description-mixed
420 refinements-to-beam-search
421 refinements-to-beam-search_3307412-Refinements_to_Beam_Search-extended-description-mixed
422 error-analysis-in-beam-search
423 error-analysis-in-beam-search_3307402-Error_analysis_in_beam_search-extended-description-mixed
424 bleu-score-optional
425 bleu-score-optional_3307397-Bleu_Score__optional_-extended-description-mixed
426 attention-model-intuition
427 attention-model-intuition_3307391-Attention_Model_Intuition-extended-description-mixed
428 clarifications-about-upcoming-attention-model-video_instructions
429 attention-model
430 attention-model_3307392-Attention_Model-extended-description-mixed
speech-recognition-audio-data
431 speech-recognition
432 speech-recognition_3307415-Speech_recognition-extended-description-mixed
433 trigger-word-detection
434 trigger-word-detection_3307389-Trigger_Word_Detection-extended-description-mixed
lecture-notes-optional
435 lecture-notes-w3_instructions
transformer-network
transformers
436 transformer-network-intuition
437 self-attention
438 multi-head-attention
439 transformer-network
lecture-notes-optional
440 lecture-notes-w4_instructions
end-of-access-to-lab-notebooks
441 important-reminder-about-end-of-access-to-lab-notebooks_instructions
conclusion
442 conclusion-and-thank-you
443 conclusion-and-thank-you_3307386-Conclusion_and_thank_you-extended-description-mixed
references-acknowledgments
444 references_instructions
445 acknowledgments_instructions
446 optional-opportunity-to-mentor-other-learners_instructions
Resources
course-acknowledgments
447 resources
Resolve the captcha to access the links!
