ApacheCN 深度学习译文集 20201229 更新
新增了七个教程:
TensorFlow 和 Keras 应用开发入门:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/begin-app-dev-tf-keras/README.md
零、前言:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/begin-app-dev-tf-keras/0.md
一、神经网络和深度学习简介:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/begin-app-dev-tf-keras/1.md
二、模型架构:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/begin-app-dev-tf-keras/2.md
三、模型评估和优化:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/begin-app-dev-tf-keras/3.md
四、产品化:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/begin-app-dev-tf-keras/4.md
TensorFlow 图像深度学习实用指南:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-dl-img-tf/README.md
零、前言:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-dl-img-tf/0.md
一、机器学习工具包:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-dl-img-tf/1.md
二、图片数据:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-dl-img-tf/2.md
三、经典神经网络:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-dl-img-tf/3.md
Python 元学习实用指南:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/README.md
零、前言:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/00.md
一、元学习导论:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/01.md
二、使用连体网络的人脸和音频识别:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/02.md
三、原型网络及其变体:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/03.md
四、使用 TensorFlow 的关系和匹配网络:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/04.md
五、记忆增强神经网络:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/05.md
六、MAML 及其变体:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/06.md
七、元 SGD 和 Reptile:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/07.md
八、作为优化目标的梯度一致性:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/08.md
九、最新进展和后续步骤:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/09.md
十、答案:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-meta-learn-py/10.md
Python 强化学习实用指南:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/README.md
零、前言:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/00.md
一、强化学习导论:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/01.md
二、OpenAI 和 TensorFlow 入门:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/02.md
三、马尔可夫决策过程与动态规划:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/03.md
四、用于游戏的蒙特卡洛方法:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/04.md
五、时间差异学习:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/05.md
六、多臂老虎机问题:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/06.md
七、深度学习基础:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/07.md
八、深度 Q 网络和 Atari 游戏:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/08.md
九、用深度循环 Q 网络玩《毁灭战士》:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/09.md
十、异步优势演员评论家网络:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/10.md
十一、策略梯度和优化:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/11.md
十二、Capstone 项目 – 将 DQN 用于赛车:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/12.md
十三、最新进展和后续步骤:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/13.md
十四、答案:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/handson-rl-py/14.md
Python 智能项目:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/README.md
零、前言:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/00.md
一、人工智能系统的基础:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/01.md
二、迁移学习:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/02.md
三、神经机器翻译:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/03.md
四、使用 GAN 的时尚行业样式迁移:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/04.md
五、视频字幕应用:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/05.md
六、智能推荐系统:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/06.md
七、电影评论情感分析移动应用:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/07.md
八、用于客户服务的会话式 AI 聊天机器人:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/08.md
九、使用强化学习的自主无人驾驶汽车:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/09.md
十、深度学习视角的验证码:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/intel-proj-py/10.md
精通 Sklearn 和 TensorFlow 预测性分析:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/master-pred-anal-sklearn-tf/README.md
零、前言:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/master-pred-anal-sklearn-tf/0.md
一、回归和分类的集成方法:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/master-pred-anal-sklearn-tf/1.md
二、交叉验证和参数调整:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/master-pred-anal-sklearn-tf/2.md
三、使用特征:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/master-pred-anal-sklearn-tf/3.md
四、人工神经网络和 TensorFlow 简介:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/master-pred-anal-sklearn-tf/4.md
五、将 TensorFlow 和深度神经网络用于预测分析:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/master-pred-anal-sklearn-tf/5.md
TensorFlow 2.0 的新增功能:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/README.md
七、从 TensorFlow 1.x 迁移到 2.0:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/7.md
五、模型推理管道 - 多平台部署:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/5.md
六、AIY 项目和 TensorFlow Lite:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/6.md
三、设计和构建输入数据管道:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/3.md
四、TensorBoard 的模型训练和使用:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/4.md
一、TensorFlow 2.0 入门:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/1.md
二、Keras 默认集成和急切执行:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/2.md
零、前言:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/0.md
第 1 部分:TensorFlow 2.0 - 架构和 API 更改:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/pt1.md
第 2 部分:TensorFlow 2.0 - 数据和模型训练管道:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/pt2.md
第 3 部分:TensorFlow 2.0 - 模型推断和部署以及 AIY:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/pt3.md
第 4 部分:TensorFlow 2.0 - 迁移,总结:https://github.com/apachecn/apachecn-dl-zh/blob/master/docs/whats-new-tf2/pt4.md