Tensorflow

使用Tensorflow解决现有的问题
Running at python3

GAN

implementation_1_GAN.ipynb 基于GAN生成对抗网络的Python实现 https://blog.csdn.net/tudaodiaozhale/article/details/84997189

implementation_2_text_classification.ipynb 基于双向LSTM(Bi-LSTM)文本分类的Tensorflow实现 https://blog.csdn.net/tudaodiaozhale/article/details/86220530

implementation_3_text_generation.ipynb 使用LSTM文本生成
implementation_3_inference.ipynb 推理(进行文本生成)

implementation_4_seq2seq.ipynb 使用序列到序列模型文本生成
implementation_4_inference.ipynb 推理

Name		Name	Last commit message	Last commit date
Latest commit History 15 Commits
MNIST_data		MNIST_data
data		data
graphs		graphs
.gitignore		.gitignore
README.md		README.md
implementation_1_GAN.ipynb		implementation_1_GAN.ipynb
implementation_2_preprocessing.ipynb		implementation_2_preprocessing.ipynb
implementation_2_text_classification.ipynb		implementation_2_text_classification.ipynb
implementation_3_inference.ipynb		implementation_3_inference.ipynb
implementation_3_text_generation.ipynb		implementation_3_text_generation.ipynb
implementation_4_inference.ipynb		implementation_4_inference.ipynb
implementation_4_seq2seq.ipynb		implementation_4_seq2seq.ipynb
setp_2_mnist_softmax_regression.ipynb		setp_2_mnist_softmax_regression.ipynb
step_1_linear_regression.ipynb		step_1_linear_regression.ipynb
step_1_my.ipynb		step_1_my.ipynb
step_2_my.ipynb		step_2_my.ipynb
step_3_minist_cnn.ipynb		step_3_minist_cnn.ipynb