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Gathers Tensorflow deep learning models.
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README.md

Deep-Learning-Tensorflow

Gathers Tensorflow deep learning projects.

Table of contents

Convolutional Neural Network

  1. Scratch Alex-net CIFAR 10
  2. Capsule Network
  3. Encoder-Decoder
  4. Residual Network
  5. Basic Conv on MNIST
  6. Byte-Net Translator
  7. Siamese Network on MNIST
  8. Generalized Hamming Network on MNIST
  9. Binary-net
  10. Kmax Conv1d
  11. Temporal Conv1d
  12. Triplet loss on MNIST
  13. Dense-net
  14. U-net

Feed-forward Neural Network

  1. Batch-normalization
  2. Encoder-Decoder
  3. Word Vector
  4. Dropout Comparison, GIF included
  5. L1, L2, L1-L2 Regularization Comparison, GIF included
  6. Optimizer Comparison (Gradient Descent, Adagrad, RMSProp, Adam), GIF included
  7. Batch-normalization Comparison, GIF included
  8. Self-Normalized without and with API on MNIST
  9. Addsign and Powersign Optimizer
  10. Backprop without Learning Rates Through Coin Betting Optimizer (COCOB)

Recurrent Neural Network

  1. Music Generator
  2. Stock forecasting, GIF included
  3. Text Generator
  4. Signal Classifier
  5. Generator Comparison (LSTM GRU, LSTM Bidirectional, GRU Bidirectional), GIF included
  6. Time-Aware Long-Short Term Memory
  7. Dilated RNN
  8. Layer-Norm LSTM
  9. Neural Turing Machine
  10. Only Attention
  11. Multihead Attention
  12. Fast-slow LSTM
  13. Siamese Network
  14. Nested LSTM
  15. DNC (Differentiable Neural Computer)
  16. Simple Recurrent Unit

Attention API

  1. Bahdanau
  2. Luong
  3. Hierarchical
  4. Additive
  5. Soft
  6. Attention-over-Attention
  7. Bahdanau API
  8. Luong API

Sequence-to-Sequence

  1. Basic Seq-to-Seq
  2. Beam decoder
  3. Chatbot with Attention (old API)
  4. Summarization with Attention (old API)
  5. Luong attention
  6. Bahdanau attention
  7. Bidirectional
  8. Estimator
  9. Altimatum (bidirectional + lstm + luong + beam)

Hybrid Model

  1. CNN + LSTM RNN for OCR
  2. GAN Sentence

Bayesian Hyperparameter Optimization

  1. Conv-CIFAR10
  2. Feedforward-Iris
  3. Recurrent-Sentiment
  4. Conv-Iceberg

Regression

  1. Linear Regression, GIF included
  2. Polynomial Regression, GIF included
  3. Ridge Regression, GIF included
  4. Lasso Regression, GIF included
  5. Elastic-net Regression, GIF included
  6. Sigmoid Regression, GIF included
  7. Quantile Regression

Reinforcement-learning

  1. Policy gradient
  2. Q-learning
  3. Double Q-learning
  4. Recurrent-Q-learning
  5. Double Recurrent-Q-learning
  6. Dueling Q-learning
  7. Dueling Recurrent-Q-learning
  8. Double Dueling Q-learning
  9. Double Dueling Recurrent-Q-learning
  10. Actor-Critic
  11. Actor-Critic Dueling
  12. Actor-Critic Recurrent
  13. Actor-Critic Dueling Recurrent
  14. Async Q-learning

Distributed

  1. TF-Distributed
  2. Sparkflow
  3. Dask Tensorflow

Miscellaneous

  1. RNN-LSTM 20newsgroup Tensorboard histrogram
  2. Tensorboard debugger
  3. Transfer learning emotion dataset on MobilenetV2
  4. Multiprocessing tfrecords
  5. TF-Serving
  6. Renaming checkpoint
  7. Load Tensorflow Slim Checkpoint
  8. Observed how Inception learned

Generative Adversarial Network

  1. DCGAN
  2. DiscoGAN
  3. Basic GAN
  4. WGAN-improve
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