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二战期间，名叫迪米特里（Alexander Mercury 饰）的莫斯科电影学院研究生有幸接到伟大领袖斯大林同志的命令，以战地摄影师的身份跟随诺维科夫（Robert Gwilym 饰）率领的侦查连队奔赴前线。他的镜头中记录了战士们闲暇的瞬间以及战场上激烈交战的情景，当然也有这些在战争洗礼中丧失人性的士兵罪恶兽性的一面。在一个天寒地冻的时节，侦察连队接到代号熊虎303小队的求救电话，诺维科夫率队启程前往对方所在的偏僻矿区。谁知那里的情景令所有人大为震惊，当地尸横遍野，几无人烟，好像不久前刚刚经历过几位惨烈的战斗。而时不时突然出现的恐怖丧尸更威胁着侦察连队的安危。　　河娜的母亲虽然自己的丈夫死了，但还是接纳河娜的姑妈和她的女儿真弥，一起生活。她开了一个小小的温泉浴场，因此认识了经常来洗澡的韩国男人，并打算和这个男人结婚。这个韩国男人就是允书的爸爸。允书在10岁时失去母亲后患上了自闭症，后来因为父亲的再婚，允书和河娜成为法律上的兄妹关系。允书按着十年前因病而去世的母亲的遗言，一下雪就想到母亲回来，因此有了赤脚跑进大雪中的习惯。河娜感觉到允书内心的伤痛后，逐渐接近他。终于让他打开紧闭着的心门，并让他的爱情苏醒。70年代末期，寡妇侯玉倩意外地捡到了一个弃婴，可侯玉倩只是街道工厂的一名普通女工，家境贫寒，况且膝下已有二子，由于生活艰辛，她只能供养一个孩子念书，如果收养了这个弃婴，日子定会雪上加霜，侯玉倩只好把弃婴送走。可事情突变，当她再次看到弃婴那种不忍目睹的凄凉景象时，善良之心又让她把弃婴重新抱回家中，决心不管生活多么艰难，也要把他抚养成人，并按照孩子名字的排序，给他取名叫窦兆辉。时光迁徙，岁月流逝，窦兆辉在侯玉倩的呵护与关怀下长大成人，成为一名出色的外科医生。在第五季中,Diane不得不扪心自问,当失去两位顶尖律师后,她帮助Liz一起管理一家非裔美国人律师事务所是否合适。Marissa和事务所与HalWackner(MandyPatinkin饰)产生了纠葛,Hal是一名芝加哥普通人,他决定在一家复印店的后院开设自己的法庭。CushJumbo和DelroyLindo确认回归首播集,客串出演Lucca和Adrian,以恰当结束各自角色的故事线。那你们意下如何呢？我们走。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 ~