Windows下离线安装TensorFlow2.0.0所需依赖包都在附件中，python3环境可以参考

使用keras实现的基于Bi-LSTM CRF的中文分词 词性标注

Attention.zip文件中总结了几种关于注意力机制的代码，有keras和tensorflow，还有PyTorch框架的

Keras【极简】seq2seq英译中示例，附带语料以及训练500次后的模型

A keras implementation of "Show, Attend and Tell: Neural Image Caption Generation with Visual Attention"

英文版PDF, 2018出版 Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You’ll then work with theories related to re inforcement learning and see the concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov’s Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI before looking at Open AI Gym. You’ll then learn about Swarm Intelligence with Python in terms of reinforcement learning. The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There’s also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you'll delve into Google’s Deep Mind and see scenarios where reinforcement learning can be used. What You'll Learn Absorb the core concepts of the reinforcement learning process Use advanced topics of deep learning and AI Work with Open AI Gym, Open AI, and Python Harness reinforcement learning with TensorFlow and Keras using Python Who This Book Is For Data scientists, machine learning and deep learning professionals, developers who want to adapt and learn reinforcement learning. Table of Contents Chapter 1: Reinforcement Learning Basics Chapter 2: RL Theory and Algorithms Chapter 3: OpenAI Basics Chapter 4: Applying Python to Reinforcement Learning Chapter 5: Reinforcement Learning with Keras, TensorFlow, and ChainerRL Chapter 6: Google’s DeepMind and the Future of Reinforcement Learning

python Keras库 安装包 Keras-2.1.2-py2.py3-none-any.whl

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 2ed 2019.pdf Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow SECOND EDITION Concepts, Tools, and Techniques to Build Intelligent Systems

pytorch的机制便于快速开发模型，但是在产品上的运用不稳定，需要将其转换为keras对应的模型权重，使用该代码进行转换的示例可见：https://blog.csdn.net/xiaoxifei/article/details/82685298

keras_分类例子，深度学习专用，代码简单，