故事讲述的是一个大家庭的长女承担起母亲的责任，含辛茹苦把弟弟妹妹们拉扯大，又在重重困难袭来之时不离不弃，维持家庭团结的故事，主人公傻春类似女版的“阿甘”，虽然看着有几分“傻”，但却一直用一颗善良和真诚的心对待这个世界，最终博得了属于自己和家人的幸福。
Considering N categories C1, C2 …, CN, the basic idea of multi-classification learning is "disassembly method", that is, multi-classification tasks are disassembled into several two-classification tasks to solve. Specifically, the problem is split first, and then a classifier is trained for each split second classification task. During the test, the prediction results of these classifiers are integrated to obtain the final multi-classification results. The key here is how to split multiple classification tasks and how to integrate multiple classifiers.
影片讲述了在某舞蹈学校中，几名参加培训的年轻男女无意触碰了恐怖“午夜十二点”的禁忌，之后他们进入了这个学校最神秘的127无人宿舍，紧接着恐怖灵异事件接连频发：白衣游魂、床下鬼手、夜半钟声纷纷显现，发疯、死亡的诅咒时刻笼罩着他们，而后他们意外得知127宿舍竟然是该学校的恐怖禁地，凡是午夜十二点接近该宿舍的人都将受到诅咒，他们能够顺利逃脱这个恐怖诅咒吗？
钱信伊：亚洲笑星闹美国. 在这部单口喜剧特辑中，钱信伊（《特雷弗·诺亚每日秀》《摘金奇缘》）登上舞台中央，并就当代美国生活等话题发表看法。
他对农事最感兴趣，又在行，我就这么比，他就不觉得这考试有啥了不得了。
他看清了眼前的这位皇帝。
MDT Team Collaboration and Culture
405 Attack 405 Force = 405* (1 +405/250) = 1061
英王府，枫园内，秦旷看了香儿的信，果然很高兴，赏了毛凡，然后就开始翻书查典，又集往日所学，形成文字，竟是做了一篇文章。
Through President Nolan's speech, the audience learned that Wilton Preparatory College, which has a 75% Ivy League graduation rate, strictly implements the "Tradition"; Honour; Discipline; Excellent "school motto. This also set an extremely depressing tone for the school early on and laid a big background for the future development of things.
长途跋涉后，浪人听到一位父亲说年轻人不听劝告去赌博，又听小酒店的权爷说两个头头间有仇，便决定在村里住下来。浪人给一方头头清兵卫以杀掉三个不合作者获银五十两为条件，当了保镖。起名叫桑烟三十郎。可是女头头阿铃，打架取胜后说要是杀了保镖，50两银子就要回来。浪人偷听后，辞去了这份工作。当保镖的本间先生，在十字路口碰上了清兵卫和新田丑寅两家，怒目而视，浪人在一旁观战。丑寅的身边虽然跟着弟弟亥之吉，但他好打架。
现在田荣开始怀疑，范文轲早早就和刘邦有了勾结，他甚至怀疑此番教唆田市调动大军反扑都是他们商议好的奸计。
20世纪50年代，日本九州香椎湾海滩，一对殉情者的尸体被人发现。男人是正陷入贪污丑闻的产建省助理科长佐山宪一（大浦龍宇一 饰），女人则是银座某酒店的酒女阿时（原沙知絵 饰）。表面上这是一起平常的畏罪殉情自杀案件，来自博多的中年警官鸟饲重太郎（北野武 饰）以及警视厅搜查二课的年轻刑警三原纪一（高桥克典 饰）却发现案件背后疑点重重。经过一番缜密调查，他们将目标牢牢锁在佐山的上司石田芳男（竹中直人 饰）和机械工具公司经理安田辰郎（柳葉敏郎 饰）身上，然而两人却有着无可辩驳的不在场证明。为了找到确凿证据，鸟饲和三原进行了艰难的取证工作，终于……
朱雀将军好厉害的样子，怪道说他是我大靖头号猛将。
章家的三朵花，一朵清香雅丽，一朵红艳脱俗，一朵最美最甜却最多刺，因上一代的恩怨，造成下一代的牵连纠结，最终酿成无法挽回的遗憾。
Deep Learning with Python: Although this is another English book, it is actually very simple and easy to read. When I worked for one year before, I wrote a summary (the "original" required bibliography for data analysis/data mining/machine learning) and also recommended this book. In fact, this book is mainly a collection of demo examples. It was written by Keras and has no depth. It is mainly to eliminate your fear of difficulties in deep learning. You can start to do it and make some macro display of what the whole can do. It can be said that this book is Demo's favorite!
Although the time of this practical activity is short, the enlightenment it leaves us is profound and long-term, and it is a solid step on our life road. Through participating in social practice activities attentively, I have known the society, realized my social position, defined my historical mission and stimulated my enthusiasm for learning. I will constantly adjust and perfect my knowledge structure, overcome various setbacks on the way forward, exercise my will and perseverance, and make preparations for adapting to future work.
Final Judgment:
惊得众人都望着小苞谷，不知为何侄儿这样怕他。
