tensorflow_practice：tensorflow实战练习，包括强化学习，推荐系统，nlp等

Tensroflow练习 ====== 相关数据集下载地址：链接:https://pan.baidu.com/s/1GMv7_3qruoVZBJMvN-afGA 密码:ako7 基于tf1.4 目录 1、基础<br> [基本语法<br>](https://github.com/princewen/tensorflow_practice/blob/master/basic/basic.py) [tensorBoard使用<br>](https://github.com/princewen/tensorflow_practice/blob/master/basic/tensorBoard.py) [dropout<br>](https://github.com/princewen/tensorflow_practice/blob/master/basic/dropout.py) [模型保存与重载<br>](https://github.com/princewen/tensorflow_practice/blob/master/basic/save2file.py) [基本神经网络<br>](https://github.com/princewen/tensorflow_practice/blob/master/basic/first_nerual_network.py) [卷积神经网络<br>](https://github.com/princewen/tensorflow_practice/blob/master/basic/CNN.py) <br> 2、自然语言相关<br> [static_RNN<br>](https://github.com/princewen/tensorflow_practice/blob/master/nlp/RNN_static_cell.py) [dynamic_RNN<br>](https://github.com/princewen/tensorflow_practice/blob/master/nlp/RNN_dynamic_cell.py) [LSTM<br>](https://github.com/princewen/tensorflow_practice/blob/master/nlp/LSTM.py) [LSTM_regression<br>](https://github.com/princewen/tensorflow_practice/blob/master/nlp/LSTM_Regression.py) [seq2seq<br>](https://github.com/princewen/tensorflow_practice/blob/master/nlp/basic_seq2seq.py) [seq2seq_attention<br>](https://github.com/princewen/tensorflow_practice/tree/master/nlp/chat_bot_seq2seq_attention) <br> 3、强化学习相关<br> [Q-learning<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/my_q_learning_new) [SARSA<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/SARSA) [SARSA-lambda<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/sarsa_lambda) [DQN<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/DQN-demo) [Double DQN<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/Double-DQN-demo) [Dueling DQN<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/Dueling%20DQN%20Demo) [Prioritized Replay DQN<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/Prioritized_Replay_DQN_demo) [Policy Gradient<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/Basic-Policy-Network) [Actor-Critic<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/Basic-Actor-Critic) [DDPG<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/Basic-DDPG) [Pointer-Network<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/myPtrNetwork) [MADDPG<br>](https://github.com/princewen/tensorflow_practice/tree/master/RL/Basic-MADDPG-Demo) <br> 4、推荐系统<br> [FM<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/recommendation-FM-demo) [FFM<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/recommendation-FFM-Demo) [DeepFM<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/Basic-DeepFM-model) [Deep Cross Network<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/Basic-DCN-Demo) [P NN<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/Basic-PNN-Demo) [NFM<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/Basic-NFM-Demo) [AFM<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/Basic-AFM-Demo) [MLR<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/Basic-MLR-Demo) [DIN<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/Basic-DIN-Demo) [Bandit<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/Basic-Bandit-Demo) [GBDT+LR<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/GBDT%2BLR-Demo) [evaluation-metrics<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/Basic-Evaluation-metrics) [NCF<br>](https://github.com/princewen/tensorflow_practice/tree/master/recommendation/Basic-NCF-Demo) <br> 5、GAN<br> [Basic GAN<br>](https://github.com/princewen/tensorflow_practice/blob/master/GAN/GAN.py) [SeqGAN<br>](https://github.com/princewen/tensorflow_practice/tree/master/GAN/seqgan) <br> <br> <br> 推荐阅读 ============== 1、基础<br> [TensorFlow基础知识点总结<br>](https://www.jianshu.com/p/ce213e6b2dc0) [用tensorboard来看看我们的网络流吧<br>](https://www.jianshu.com/p/41466470b347) [使用dropout来避免过拟合吧<br>](https://www.jianshu.com/p/4f1b525ddf86) [使用Tensorflow实现第一个神经网络吧！<br>](https://www.jianshu.com/p/596a30d46f34y) [实现CNN对mnist手写数字分类<br>](https://www.jianshu.com/p/49ab6568e472) <br> 2、自然语言相关<br> [使用简单的RNN观测数字中的规律<br>](https://www.jianshu.com/p/3ccc1eb5fda2) [更进一步，使用LSTM实现对手写数字识别<br>](https://www.jianshu.com/p/d25baccde6bc) [简单的Seq2Seq实现作对联<br>](https://www.jianshu.com/p/83443b2baf27) [使用Seq2Seq+attention model实现简单的Chatbot<br>](https://www.jianshu.com/p/aab40f439012) <br> 3、强化学习相关<br> [实战深度强化学习DQN-理论和实践<br>](https://www.jianshu.com/p/10930c371cac) [DQN三大改进(一)-Double DQN<br>](https://www.jianshu.com/p/fae51b5fe000) [DQN三大改进(二)-Prioritised replay<br>](https://www.jianshu.com/p/db14fdc67d2c) [DQN三大改进(三)-Dueling Network<br>](https://www.jianshu.com/p/b421c85796a2) [深度强化学习-Policy Gradient基本实现<br>](https://www.jianshu.com/p/2ccbab48414b) [深度强化学习-Actor-Critic算法原理和实现<br>](https://www.jianshu.com/p/6fe18d0d8822) [深度强化学习-DDPG算法原理和实现<br>](https://www.jianshu.com/p/6fe18d0d8822) [Pointer-network理论及tensorflow实战<br>](https://www.jianshu.com/p/2ad389e91467) [探秘多智能体强化学习-MADDPG算法原理及简单实现<br>](https://www.jianshu.com/p/4e4e35d80137) <br> 4、推荐系统<br> [推荐系统遇上深度学习(一)--FM模型理论和实践<br>](https://www.jianshu.com/p/152ae633fb00) [推荐系统遇上深度学习(二)--FFM模型理论和实践<br>](https://www.jianshu.com/p/781cde3d5f3d) [推荐系统遇上深度学习(三)--DeepFM模型理论和实践<br>](https://www.jianshu.com/p/6f1c2643d31b) [推荐系统遇上深度学习(四)--多值离散特征的embedding解决方案<br>](https://www.jianshu.com/p/4a7525c018b2) [推荐系统遇上深度学习(五)--Deep&Cross Network模型理论和实践<br>](https://www.jianshu.com/p/77719fc252fa) [推荐系统遇上深度学习(六)--PNN模型理论和实践<br>](https://www.jianshu.com/p/be784ab4abc2) [推荐系统遇上深度学习(七)--NFM模型理论和实践<br>](https://www.jianshu.com/p/4e65723ee632) [推荐系统遇上深度学习(八)--AFM模型理论和实践<br>](https://www.jianshu.com/p/83d3b2a1e55d) [推荐系统遇上深度学习(九)--评价指标AUC原理及实践<br>](https://www.jianshu.com/p/4dde15a56d44) [推荐系统遇上深度学习(十)--GBDT+LR融合方案实战<br>](https://www.jianshu.com/p/96173f2c2fb4) [推荐系统遇上深度学习(十一)--神经协同过滤NCF原理及实战<br>](https://www.jianshu.com/p/6173dbde4f53) [推荐系统遇上深度学习(十二)--推荐系统中的EE问题及基本Bandit算法<br>](https://www.jianshu.com/p/95b2de50ce44) [推荐系统遇上深度学习(十三)--linUCB方法浅析及实现<br>](https://www.jianshu.com/p/e0e843d78e3c) [推荐系统遇上深度学习(十四)--《DRN:A Deep Reinforcement Learning Framework for News Recommendation》<br>](https://www.jianshu.com/p/c0384b213320) [推荐系统遇上深度学习(十五)--强化学习在京东推荐中的探索<br>](https://www.jianshu.com/p/b9113332e33e) [推荐系统遇上深度学习(十六)--详解推荐系统中的常用评测指标<br>](https://www.jianshu.com/p/665f9f168eff) [推荐系统遇上深度学习(十七)--探秘阿里之MLR算法浅析及�