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nav:
- Home: index.md
- Why use Keras: why-use-keras.md
- Getting started:
- Guide to the Sequential model: getting-started/sequential-model-guide.md
- Guide to the Functional API: getting-started/functional-api-guide.md
- FAQ: getting-started/faq.md
- Models:
- About Keras models: models/about-keras-models.md
- Sequential: models/sequential.md
- Model (functional API): models/model.md
- Layers:
- About Keras layers: layers/about-keras-layers.md
- Core Layers: layers/core.md
- Convolutional Layers: layers/convolutional.md
- Pooling Layers: layers/pooling.md
- Locally-connected Layers: layers/local.md
- Recurrent Layers: layers/recurrent.md
- Embedding Layers: layers/embeddings.md
- Merge Layers: layers/merge.md
- Advanced Activations Layers: layers/advanced-activations.md
- Normalization Layers: layers/normalization.md
- Noise layers: layers/noise.md
- Layer wrappers: layers/wrappers.md
- Writing your own Keras layers: layers/writing-your-own-keras-layers.md
- Preprocessing:
- Sequence Preprocessing: preprocessing/sequence.md
- Text Preprocessing: preprocessing/text.md
- Image Preprocessing: preprocessing/image.md
- Losses: losses.md
- Metrics: metrics.md
- Optimizers: optimizers.md
- Activations: activations.md
- Callbacks: callbacks.md
- Datasets: datasets.md
- Applications: applications.md
- Backend: backend.md
- Initializers: initializers.md
- Regularizers: regularizers.md
- Constraints: constraints.md
- Visualization: visualization.md
- Scikit-learn API: scikit-learn-api.md
- Utils: utils.md
- Contributing: contributing.md
- Examples:
- Addition RNN: examples/addition_rnn.md
- Custom layer - antirectifier: examples/antirectifier.md
- Baby RNN: examples/babi_rnn.md
- Baby MemNN: examples/babi_memnn.md
- CIFAR-10 CNN: examples/cifar10_cnn.md
- CIFAR-10 ResNet: examples/cifar10_resnet.md
- Convolution filter visualization: examples/conv_filter_visualization.md
- Convolutional LSTM: examples/conv_lstm.md
- Deep Dream: examples/deep_dream.md
- Image OCR: examples/image_ocr.md
- Bidirectional LSTM: examples/imdb_bidirectional_lstm.md
- 1D CNN for text classification: examples/imdb_cnn.md
- Sentiment classification CNN-LSTM: examples/imdb_cnn_lstm.md
- Fasttext for text classification: examples/imdb_fasttext.md
- Sentiment classification LSTM: examples/imdb_lstm.md
- Sequence to sequence - training: examples/lstm_seq2seq.md
- Sequence to sequence - prediction: examples/lstm_seq2seq_restore.md
- Stateful LSTM: examples/lstm_stateful.md
- LSTM for text generation: examples/lstm_text_generation.md
- Auxiliary Classifier GAN: examples/mnist_acgan.md
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