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大家聚会做诗谈笑，都十分和睦。Ichabod Crane是美国独立战争时期的一个上尉。他自称去过地狱，然后又回来了——但不是回到他自己的时代，而是回到了250年之后的现代沉睡谷。他带来了一个惊人的秘密——这个秘密甚至可以回溯到美国独立之初，那些开国元勋（国父，签署《独立宣言》和《美国宪法》的政治领导人以及参与美国革命的领袖）全都与之有关。卫讼师顿时面色憋得紫涨，因为二太太身边死了一个丫头一个婆子。不禁好笑，项羽的女人你也敢打主意。Sorry to force a wave of chicken soup. Originally, I planned to write a machine learning series last year, but after writing three articles for work and physical reasons, there was no more. In the first half of this year, I was tired to death after doing a big project. In the second half of this year, I just took a breath of relief, so the follow-up that I owed before will definitely continue to be even more. In order not to let everyone worship blindly, I decided to write a series of in-depth study, one article per week, which will end in about three months. Teach Xiaobai how to get started. And finished! All! No! Fei! ! It is not simply to write demo and tuning parameters that are available on the Internet. Reject demo, start with me! If you don't understand, please leave a message under my article. I will try my best to reply when I see it. This series will mainly adopt the in-depth learning framework of PaddlaPaddle, and will compare the advantages and disadvantages of Keras, TensorFlow and MXNET (because I have only used these four frameworks, there are too many people writing TensorFlow, and I am using PaddlePaddle well at present, so I decided to start with this). All codes will be put on github (link: https://github.com/huxiaoman7/PaddlePaddle_code). Welcome to mention issue and star. At present, only the first article () has been written, and there will be more in-depth explanation and code later. At present, I have made a simple outline. If you are interested in the direction, you can leave me a message, and I will refer to the addition ~主角放荡不羁，爽朗豁达，豪迈潇洒，天生侠义心肠，并且深情不移。为了寻找下落不明的太子（图特哈蒙 配音），大护法（小连杀 配音）来到了一个诡异而又古怪的小镇上，在那里居住着一群不会说话的花生人，它们夜夜点燃来路不明的油灯，将天上漂浮的巨大花生熏得黑漆漆的。