Deep-Learning-Specialization
Coursera's Deep Learning Specialization offered by deeplearning.ai.
파일 탐색기
- 2layerNN.png
- 2layerNN_kiank.png
- backpass.png
- backprop.png
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- classification_kiank.png
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- sgd.gif
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- Building_your_Deep_Neural_Network_Step_by_Step.ipynb
- Deep Neural Network - Application.ipynb
- Logistic_Regression_with_a_Neural_Network.ipynb
- Planar_data_classification_with_one_hidden_layer.ipynb
- Python_Basics_with_Numpy.ipynb
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- Lecture01_ Basics of Neural Network Programming.pdf
- Lecture02_One hidden layer Neural Network.pdf
- Lecture03_Deep L-layer Neural Network.pdf
- Readme.md
- 1Dgrad_kiank.png
- cost.jpg
- dictionary_to_vector.png
- dropout1_kiank.mp4
- dropout2_kiank.mp4
- field_kiank.png
- handbackward_kiank.png
- handforward_kiank.png
- hands.png
- kiank_minibatch.png
- kiank_partition.png
- kiank_sgd.png
- kiank_shuffle.png
- lr.png
- Momentum.png
- NDgrad_kiank.png
- onehot.png
- opt1.gif
- opt2.gif
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- thumbs_up.jpg
- Gradient_Checking.ipynb
- Initialization.ipynb
- Optimization_Algorithms.ipynb
- Regularization.ipynb
- Tensorflow_Introduction.ipynb
- 01-_Bias_-_Variance.png
- 02-_Early_stopping.png
- 03-_Numerical_approximation_of_gradients.png
- 04-_batch_vs_mini_batch_cost.png
- 05-_exponentially_weighted_averages_intuitions.png
- 06-_RMSprop.png
- 07-_softmax.png
- 08-_Momentum.png
- 09-_Tuning.png
- 10-_PandaCaviar.png
- bn.png
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- softmax_regression.png
- Lecture01_Regularization and Gradient Checking.pdf
- Lecture02_Optimization Algorithms.pdf
- Lecture03_Hyperparameter tuning and Batch Normalization.pdf
- Readme.md
- Case Study 1 - Bird Recognition in the City of Peacetopia.pdf
- Case Study 2 - Autonomous Driving.pdf
- 01-_Why_human-level_performance.png
- Lecture01 - ML Strategy 1.pdf
- Lecture02 - ML Strategy 2.pdf
- Readme.md
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- cat.jpg
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- content.jpeg
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- conv.png
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- conv_kiank.mp4
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- Convolution_schematic.gif
- dan.jpg
- danielle.png
- decoder.png
- distance_kiank.png
- distance_matrix.png
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- encoder.png
- f_x.png
- felix.jpg
- gram.png
- hidden_layers.png
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- inception_block1a.png
- kevin.jpg
- kian.jpg
- louvre.jpg
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- max_pool.png
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- mobilenetv2.png
- model.png
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- my_image.jpg
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- my_image_5.jpeg
- NST_GM.png
- NST_LOSS.png
- PAD.png
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- persian_cat.jpg
- persian_cat_content.jpg
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- pixel_comparison.png
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- resnet_kiank.png
- result.png
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- sebastiano.jpg
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- SIGNS.png
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- snowalpaca.png
- stone_style.jpg
- style300.jpg
- thumbs_up.jpg
- tian.jpg
- triplet_comparison.png
- unet.png
- vanishing_grad_kiank.png
- vert_horiz_kiank.png
- younes.jpg
- anchor_map.png
- architecture.png
- box_label.png
- flatten.png
- iou.png
- non-max-suppression.png
- proba_map.png
- probability_extraction.png
- Art_Generation_with_Neural_Style_Transfer.ipynb
- Convolution_model_Application.ipynb
- Convolution_model_Step_by_Step.ipynb
- Face_Recognition_with_One_shot_Learning.ipynb
- Image_segmentation_with_U-Net.ipynb
- Residual_Networks.ipynb
- Transfer_learning_with_MobileNet.ipynb
- YOLO_Car_detection.ipynb
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- 3D_conv.png
- 3D_conv_multiple.png
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- 45.gif
- Classification.jpg
- ClassificationLoc.jpg
- decoder.png
- depth_conv.png
- depth_sep_conv.png
- EfficientNet.png
- encoder.png
- gram1.png
- gram2.png
- inception_block1a.png
- InstanceSegmentation.png
- J_style_l.png
- Labels_pixel_1.png
- Labels_pixel_2.png
- MobileNet.png
- MobileNet_v2_bn.png
- normal_conv.png
- ObjectDetection.png
- OD_SS.png
- point_conv.png
- receptiveField.png
- resNet.jpg
- Segmentation_Architecture_1.png
- Segmentation_Architecture_2.png
- Semantic_Segmentation_NN_1.png
- Semantic_Segmentation_NN_2.png
- SemanticSegmentation.png
- TL1.png
- TL2.png
- TL3.png
- Transpose_Conv_1.png
- Transpose_Conv_2.png
- Transpose_Conv_3.png
- Transpose_Conv_4.png
- U-Net_Architecture.png
- unet.png
- vertical_kernel.png
- Lecture01_Convolutional Neural Networks.pdf
- Lecture02_Deep CNN Models.pdf
- Lecture03_Object Detection.pdf
- Lecture04 - One-shot Learning & Neural Style Transfer.pdf
- Readme.md
- 1-hot-vector.png
- attn_mechanism.png
- attn_model.png
- clip.png
- cosine_sim.png
- data_set.png
- dataset_kiank.png
- date_attention.png
- date_attention2.png
- decoder.png
- decoder_layer.png
- dino.jpg
- dinos3.png
- emb_kiank.png
- embedding1.png
- emo_model.png
- emojifier-v2.png
- emojifierv1.png
- emojify_model.png
- emojiss.png
- encoder.png
- encoder_layer.png
- equalize10.png
- image_1.png
- initial_state.png
- jazz.jpg
- label_diagram.png
- lookup.png
- LSTM.png
- LSTM_cell_backward_rev3a_5.png
- LSTM_cell_backward_rev3a_c2.png
- LSTM_figure4_v3a.png
- LSTM_rnn.png
- mangosaurus.jpeg
- model.png
- music_gen.png
- music_generation.png
- neutral.png
- neutralize.png
- neutralize_kiank.png
- ones_reference.png
- poorly_trained_model.png
- RNN.png
- rnn.png
- rnn_backward_overview_3a_1.png
- rnn_cell_backprop.png
- rnn_cell_backward_3a_4.png
- rnn_cell_backward_3a_c.png
- rnn_forward_sequence_figure3_v3a.png
- rnn_step_forward.png
- rnn_step_forward_figure2_v3a.png
- self-attention.png
- shakespeare.jpg
- sound.png
- spectrogram.png
- table.png
- train_label.png
- train_reference.png
- transformer.png
- Building_a_Recurrent_Neural_Network_Step_by_Step.ipynb
- Dinosaurus_Island_Character_level_language_model.ipynb
- Embedding_plus_Positional_encoding.ipynb
- Emojify.ipynb
- Improvise_a_Jazz_Solo_with_an_LSTM_Network.ipynb
- Neural_machine_translation_with_attention.ipynb
- Operations_on_word_vectors.ipynb
- QA_dataset.ipynb
- Transformer_application_Named_Entity_Recognition.ipynb
- Transformers Architecture with TensorFlow.ipynb
- Trigger_word_detection.ipynb
- 01.png
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- 03_learning.png
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- 05_cell.png
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- Beam_search_1.png
- Beam_search_2.png
- Beam_search_3.png
- Lecture01_Recurrent Neural Network.pdf
- Lecture02_Word Embeddings.pdf
- Lecture03_Sequence model and Attention mechanism.pdf
- Lecuture04_Transformer Network.pdf
- Readme.md
- Deep Learning Course Notes.pdf
- Deep Learning Notation.pdf
- README.md
# CDN으로 사용하기
jsDelivrjsDelivr는 공개 GitHub 리포지토리를 별도 설정 없이 CDN으로 즉시 서빙합니다. 버전과 파일을 고르면 웹페이지에 바로 붙일 수 있는 링크와 예시 코드가 만들어집니다.
링크
예시
// repository documentation
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