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Foreword
One of the most nerve-wracking periods when releasing the first version of an open source project occurs when the gitter community is created. You are all alone, eagerly hoping and wishing for the first user to come along. I still vividly remember those days.
最让人紧张的时刻是当我为自己的开源项目发布第一个版本并在gitter里开放一个聊天社区，而里面只有你一个人，饥渴地期待第一个进入聊天室的用户，我仍然清楚地记得那个时期。
TensorFlow.NET is my third open source project. BotSharp and NumSharp are the first two. The response is pretty good. I also got a lot of stars on github. Although the first two projects are very difficult, I can't admit that TensorFlow.NET is much more difficult than the previous two, and it is an area I have never been involved with. Mainly related to GPU parallel computing, distributed computing and neural network model. When I started writing this project, I was also sorting out the idea of the coding process. TensorFlow is a huge and complicated project, and it is easy to go beyond the scope of personal ability. Therefore, I want to record the thoughts at the time as much as possible. The process of recording and sorting clears the way of thinking.
TensorFlow.NET是我写的第3个开源项目，BotSharp和NumSharp是前两个，反应都还不错，在github上也收获了不少星。虽然前两个项目的难度很大，但是我不得承认TensorFlow.NET的难度要比之前两个要大的多，是我从未涉入过的领域。主要涉及GPU并行计算，分布式计算和神经网络模型。当我开始写这个项目的时候，我同时也在整理编码过程时候的想法，TensorFlow是个巨大最复杂的工程，很容易超出个人能力范围，所以想尽可能地把当时的思路记录下来，也想趁着记录整理的过程把思路理清。
All the examples in this book can be found in the github repository of TensorFlow.NET. When the source code and the code in the book are inconsistent, please refer to the source code. The sample code is typically located in the Example or UnitTest project.
本书中的所有例子都可以在TensorFlow.NET的github仓库中找到，当源代码和书中的代码不一致时，请以源代码为准。示例代码一般都位于Example或者是UnitTest项目里。