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@@ -76,7 +76,7 @@ The following examples are coming from [TFLearn](https://github.com/tflearn/tfle
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-[City Name Generation](https://github.com/tflearn/tflearn/blob/master/examples/nlp/lstm_generator_cityname.py). Generates new US-cities name, using LSTM network.
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-[Shakespeare Scripts Generation](https://github.com/tflearn/tflearn/blob/master/examples/nlp/lstm_generator_shakespeare.py). Generates new Shakespeare scripts, using LSTM network.
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-[Seq2seq](https://github.com/tflearn/tflearn/blob/master/examples/nlp/seq2seq_example.py). Pedagogical example of seq2seq reccurent network. See [this repo](https://github.com/ichuang/tflearn_seq2seq) for full instructions.
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-[CNN Seq](https://github.com/tflearn/tflearn/blob/master/examples/nlp/cnn_sequence_classification.py). Apply a 1-D convolutional network to classify sequence of words from IMDB sentiment dataset.
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-[CNN Seq](https://github.com/tflearn/tflearn/blob/master/examples/nlp/cnn_sentence_classification.py). Apply a 1-D convolutional network to classify sequence of words from IMDB sentiment dataset.
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### Reinforcement Learning
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-[Atari Pacman 1-step Q-Learning](https://github.com/tflearn/tflearn/blob/master/examples/reinforcement_learning/atari_1step_qlearning.py). Teach a machine to play Atari games (Pacman by default) using 1-step Q-learning.
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