├── CONTRIBUTING ├── Convolutional Neural Networks ├── README.md ├── Week 1 │ ├── Convolution model - Application - v1.ipynb │ ├── Convolution+model+-+Step+by+Step+-+v2.ipynb │ ├── cnn_utils.py │ └── images │ │ ├── Convolution_schematic.gif │ │ ├── PAD.png │ │ ├── SIGNS.png │ │ ├── a_pool.png │ │ ├── ave-pool.png │ │ ├── ave_pool1.png │ │ ├── average_pool.png │ │ ├── conv.png │ │ ├── conv1.png │ │ ├── conv_kiank.mp4 │ │ ├── conv_nn.png │ │ ├── max_pool.png │ │ ├── max_pool1.png │ │ ├── model.png │ │ ├── thumbs_up.jpg │ │ └── vert_horiz_kiank.png ├── Week2 │ ├── KerasTutorial │ │ ├── Keras+-+Tutorial+-+Happy+House+v2.ipynb │ │ ├── images │ │ │ ├── HappyModel.png │ │ │ ├── happy-house.jpg │ │ │ └── house-members.png │ │ └── kt_utils.py │ └── ResNets │ │ ├── Residual+Networks+-+v2.ipynb │ │ ├── images │ │ ├── convblock_kiank.png │ │ ├── idblock2_kiank.png │ │ ├── idblock3_kiank.png │ │ ├── my_image.jpg │ │ ├── resnet_kiank.png │ │ ├── signs_data_kiank.png │ │ ├── skip_connection_kiank.png │ │ └── vanishing_grad_kiank.png │ │ └── resnets_utils.py ├── Week3 │ └── Car Detection for Autonomous Driving │ │ ├── Autonomous+driving+application+-+Car+detection+-+v3.ipynb │ │ ├── Drive.ai+Dataset+Sample+LICENSE │ │ ├── LICENSE │ │ ├── model_data │ │ ├── coco_classes.txt │ │ ├── object_classes.txt │ │ └── yolo_anchors.txt │ │ ├── nb_images │ │ ├── anchor_map.png │ │ ├── architecture.png │ │ ├── box_label.png │ │ ├── driveai.png │ │ ├── flatten.png │ │ ├── iou.png │ │ ├── non-max-suppression.png │ │ ├── proba_map.png │ │ └── probability_extraction.png │ │ ├── out │ │ ├── 0001.jpg │ │ ├── 0010.jpg │ │ ├── 0015.jpg │ │ └── test.jpg │ │ ├── utils.py │ │ ├── yadk │ │ ├── models │ │ │ ├── keras_darknet19.py │ │ │ └── keras_yolo.py │ │ └── utils │ │ │ └── utils.py │ │ └── yolo_utils.py └── Week4 │ ├── Face Recognition │ ├── Face+Recognition+for+the+Happy+House+-+v2.ipynb │ ├── Face+Recognition+for+the+Happy+House+-+v3.ipynb │ ├── fr_utils.py │ └── inception_blocks_v2.py │ └── Neural Style Transfer │ ├── Art+Generation+with+Neural+Style+Transfer+-+v2.ipynb │ └── nst_utils.py ├── Improving Neural Networks ├── README.md ├── Week 1 │ ├── Gradient Checking │ │ ├── Gradient+Checking+v1.ipynb │ │ ├── gc_utils.py │ │ ├── images │ │ │ ├── 1Dgrad_kiank.png │ │ │ ├── NDgrad_kiank.png │ │ │ ├── dictionary_to_vector.png │ │ │ ├── handbackward_kiank.png │ │ │ └── handforward_kiank.png │ │ └── testCases.py │ ├── Initialization │ │ ├── Initialization.ipynb │ │ └── init_utils.py │ └── Regularization │ │ ├── Regularization+-+v2.ipynb │ │ ├── datasets │ │ ├── data.mat │ │ ├── test_catvnoncat.h5 │ │ └── train_catvnoncat.h5 │ │ ├── images │ │ ├── dropout1_kiank.mp4 │ │ ├── dropout2_kiank.mp4 │ │ └── field_kiank.png │ │ ├── reg_utils.py │ │ └── testCases.py ├── Week 2 │ ├── Optimization+methods.ipynb │ ├── datasets │ │ └── data.mat │ ├── images │ │ ├── Momentum.png │ │ ├── cost.jpg │ │ ├── kiank_minibatch.png │ │ ├── kiank_partition.png │ │ ├── kiank_sgd.png │ │ ├── kiank_shuffle.png │ │ ├── opt1.gif │ │ ├── opt2.gif │ │ └── opt_momentum.png │ ├── opt_utils.py │ └── testCases.py └── Week 3 │ ├── Tensorflow+Tutorial.ipynb │ ├── datasets │ ├── test_signs.h5 │ └── train_signs.h5 │ ├── images │ ├── hands.png │ ├── onehot.png │ └── thumbs_up.jpg │ ├── improv_utils.py │ └── tf_utils.py ├── LICENSE ├── Neural Networks and Deep Learning ├── Notation Sheet.pdf ├── README.md ├── Video Notes │ ├── Binary_Classification.pdf │ ├── Logistic_Regression.pdf │ └── Logistic_Regression_Cost_Function.pdf ├── Week 2 │ ├── Logistic Regression as a Neural Network │ │ ├── .ipynb_checkpoints │ │ │ └── Logistic Regression with a Neural Network mindset v5-checkpoint.ipynb │ │ ├── Logistic Regression with a Neural Network mindset v5.ipynb │ │ ├── __pycache__ │ │ │ └── lr_utils.cpython-35.pyc │ │ ├── datasets │ │ │ ├── test_catvnoncat.h5 │ │ │ └── train_catvnoncat.h5 │ │ ├── images │ │ │ ├── LogReg_kiank.png │ │ │ ├── cat_in_iran.jpg │ │ │ ├── gargouille.jpg │ │ │ ├── image1.png │ │ │ ├── image2.png │ │ │ ├── la_defense.jpg │ │ │ ├── my_image.jpg │ │ │ └── my_image2.jpg │ │ └── lr_utils.py │ └── Python Basics with Numpy │ │ ├── .ipynb_checkpoints │ │ └── Python Basics With Numpy v3-checkpoint.ipynb │ │ ├── Python Basics With Numpy v3.ipynb │ │ └── images │ │ ├── Sigmoid.png │ │ ├── image2vector.png │ │ └── image2vector_kiank.png ├── Week 3 │ └── Planar data classification with one hidden layer │ │ ├── Planar data classification with one hidden layer v5.ipynb │ │ ├── images │ │ ├── classification_kiank.png │ │ ├── grad_summary.png │ │ ├── sgd.gif │ │ └── sgd_bad.gif │ │ ├── planar_utils.py │ │ └── testCases_v2.py ├── Week 4 │ ├── Building your Deep Neural Network - Step by Step │ │ ├── .ipynb_checkpoints │ │ │ └── Building your Deep Neural Network - Step by Step v8-checkpoint.ipynb │ │ ├── Building your Deep Neural Network - Step by Step v8.ipynb │ │ ├── __pycache__ │ │ │ ├── dnn_utils_v2.cpython-35.pyc │ │ │ ├── dnn_utils_v2.cpython-36.pyc │ │ │ ├── testCases_v4.cpython-35.pyc │ │ │ └── testCases_v4.cpython-36.pyc │ │ ├── dnn_utils_v2.py │ │ ├── images │ │ │ ├── 2layerNN.png │ │ │ ├── NlayerNN.png │ │ │ ├── backpass.png │ │ │ ├── backprop.png │ │ │ ├── backprop_kiank.png │ │ │ ├── final outline.png │ │ │ ├── imvector.png │ │ │ ├── linearback_kiank.png │ │ │ ├── mn_backward.png │ │ │ ├── model_architecture2.png │ │ │ ├── model_architecture_kiank.png │ │ │ ├── n_model_backward.png │ │ │ ├── nm_backward.png │ │ │ ├── relu.png │ │ │ └── structure.png │ │ ├── testCases_v3.py │ │ └── testCases_v4.py │ └── Deep Neural Network Application_ Image Classification │ │ ├── .ipynb_checkpoints │ │ └── Deep Neural Network - Application v8-checkpoint.ipynb │ │ ├── Deep Neural Network - Application v8.ipynb │ │ ├── __pycache__ │ │ ├── dnn_app_utils_v3.cpython-35.pyc │ │ └── dnn_app_utils_v3.cpython-36.pyc │ │ ├── datasets │ │ ├── test_catvnoncat.h5 │ │ └── train_catvnoncat.h5 │ │ ├── dnn_app_utils_v2.py │ │ ├── dnn_app_utils_v3.py │ │ └── images │ │ ├── 2layerNN_kiank.png │ │ ├── 3.jpg │ │ ├── LlayerNN_kiank.png │ │ ├── a.jpg │ │ ├── alpca.jpg │ │ ├── b.jpg │ │ ├── f.jpg │ │ ├── imvector.png │ │ ├── imvectorkiank.png │ │ ├── my_image.jpg │ │ └── untitled.txt └── readonly │ └── week3 │ └── images │ └── FlowerModel.png ├── README.md └── Sequence Models ├── README.md ├── Week 1 ├── Building a RNN step by step │ ├── Building+a+Recurrent+Neural+Network+-+Step+by+Step+-+v3.ipynb │ ├── data │ │ └── input.txt │ ├── rnn_utils.py │ ├── shakespeare.txt │ └── utils.py ├── Dinosaur Island │ ├── Dinosaurus+Island+--+Character+level+language+model+final+-+v3.ipynb │ ├── dinos.txt │ ├── shakespeare.txt │ ├── shakespeare_utils.py │ └── utils.py └── Jazz Improvisation with LSTM │ ├── Improvise+a+Jazz+Solo+with+an+LSTM+Network+-+v3.ipynb │ ├── data │ ├── 30s_seq.mp3 │ ├── 30s_trained_model.mp3 │ ├── deepjazz_on_metheny...128_epochs.midi │ ├── original_metheny.mid │ └── training_example.mp3 │ ├── data_utils.py │ ├── grammar.py │ ├── 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