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故事主要讲述了女主角桃园奈奈生因好赌而欠债的父亲不知去向， 被讨债的人赶出了家。在走投无路之时，她帮助了一位被狗追的懦怯的男人，得知她的遭遇后神秘的男人说出了「我把我的家转让给你吧。」这样出奇的话。无家可归的奈奈生虽然半信半疑，但还是前往了男人所说的住所……到了那儿发现那是一间荒废的神社。那懦怯的男人的正体正是离家出走的土地神。作为神社转让的代价，奈奈生开始了当土地神的新生活。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 ~这部电影是在蝎子的复仇之后拍摄的，英雄们被邵康袭击，这将迫使“热登和他的战士们达成一项协议，在决定王国命运的最后一场凡人快击中展开竞争。”这将迫使好人前往外部世界保卫地球王国，而蝎子则前往寻找卡米杜古（由全能的老神制造的神秘遗迹），然后再将其带回地球神秘的人，他会毁灭宇宙。从小单身从没恋爱过的女大学生，与偶然拿回家的广告牌中跳出来的偶像明星，玩起了暧昧。Show System该剧改编自秦明文学作品《法医秦明之无声的证词》，讲述了初出茅庐的天赋青年秦明（张雨剑 饰），在林当（周雨彤 饰）等人的帮助下，一步步走出童年记忆阴霾，并成长为可以把控全局的法医大神的故事。