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但是，这种癖好被认为是“媚态”、“粗野”，在打工的家庭餐厅里被同事讨厌，被店长误认为是有好感，每天都会受伤。无论外面多么喧闹，一对新人却闹中取静，双双脱离此情此景，仿佛跟多年前一样，暮色降临，相伴归家。ラプチェアー 南果歩 石橋　保　　“急冻人”原是一个科学奇才，但一次意外却令他只能靠急救机器为生。更为糟糕的是，除非他将整个高谭市的温度保持在零度以下，否则他心爱的妻子将永远不能醒来。“急冻人”开始一步步建立自己的冷冻王国，蝙蝠侠将是这个计划的最大阻碍，“急冻人”迫切需要除掉这个眼中钉。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 ~Stored procedure: (Delete after one year according to the difference between the current time and the time of entering the blacklist)