Attention-model-for-speech-recognition.png
CTC-for-speech-recognition.png
Convolution_schematic.gif
Different_train_test_dist.png
Gradient-Descent-with-Momentum.png
Neural-language-model.png
RNN-sentiment-classification.png
Recurrent-Neural-Network.png
Recurrent-Neural-Network_compact.png
Simple-sentiment-classification-model.png
Trigger-word-detection-algorithm.png
Why-do-residual-networks-work.jpg
arbitrary_padding_no_strides.gif
arbitrary_padding_no_strides_transposed.gif
architecture_programming_yolo.png
attention_model_intuition.png
bidirectionalRNN_arch.png
full_padding_no_strides.gif
full_padding_no_strides_transposed.gif
language-model-RNN-example.png
machinetranslationmodel.png
no_padding_no_strides.gif
no_padding_no_strides_transposed.gif
no_padding_strides_transposed.gif
padding_strides_odd_transposed.gif
padding_strides_transposed.gif
random_initialization.png
same_padding_no_strides.gif
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training-with-mini-batch-gradient-descent.png
1.1 Introduction to deep learning.md
1.2 Logistic regression as a neural network.md
1.3 Shallow neural networks.md
1.4 Deep Neural networks.md
2.1 Practical aspects of DL.md
2.3 Hyperparameter tuning.md
4.4 Special applications.md
5.2 Natural Language Processing & Word Embeddings.md
5.3 Sequence models & Attention mechanism.md
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