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 ~
When many salesmen start to do business, they are often very energetic. They don't know what to do when they find customers, send samples and quote prices. They often lose all their achievements. In fact, you should keep asking him, when will your order come down, and keep asking him until there is a result. In fact, purchasing is waiting for us to ask him, just like a child does not cry, how do we know he is hungry?
现在想要随心所欲地选择，却有无数阻碍横亘在面前。
Attack a king
After he went to the scene, some investors had already arrived at the scene:
由 川原砾所著、abec 绘制插图的轻小说作品《刀剑神域》系列衍伸，剧场版最新作品《刀剑神域 Progressive 无星夜的咏叹调》，官方于今日宣布电影将于 10 月在日本上映的消息。“《刀剑神域剧场版 进击篇 无星之夜的咏叹调》是以《刀剑神域》系列中“艾恩葛朗特”篇作为原型的小说《Sword Art Online 刀剑神域 Progressive》改编，也是睽违 3 年后再度推出的剧场版作品。
本作品描绘了京都府警本部新设立的“网络综合犯罪系”的活跃表现。以主任安洛一诚为首的团队，利用网络分析和职业归档等最先进的机器和技术，对抗逼近身边的网络犯罪。
Reactor Mode Process
《椿文具店~镰仓代笔物语~》是NHK电视台2017春季档日剧。以日本古都镰仓为舞台，讲述以代写书信维生的年轻女性成长的故事。主人公鸠子时隔八年回到故乡，继承去世祖母的“椿文具店”，尽管小店名字是文具店，实际上却是一家“代书铺”，带人写漂亮的文字，代书新人鸠子在这里发挥她的才能，接受各种不同的书信委托，小小的幸福让鸠子感到很充实，开始了与以往不同的新人生。由多部未华子主演，2017年4月14日播出。
翻拍自70年代的同名电视连续剧。描绘了1930年代伦敦市政厅的生活。“楼下”的仆人和“楼上”的主人的生活紧密的联系在一起。
Information on Indoor and Outdoor Fire Fighting Facilities
一部由罗棋导演，向华强、李家鼎、洪金宝主演的动作老片……
讲述了特种兵王周扬、肖克二人在对边境黑势力清剿活动中，因战友惨死，陷入深深的不安和自责中进而消极颓废，却最终在面对黑势力的反扑中两位兵王再度联手，与黑势力展开了正义与邪恶的终极对决。
出现的，是与Alata一模一样的神秘食物身姿的男人。
通过以另一个人的身份活下来的女人和真切关注她的男人之间的故事剖析人生真谛。隐藏自己的身份，嫁做财阀世家媳妇的卞智淑（秀爱饰）、愿意无条件去守护心爱女子的崔珉宇（朱智勋饰）、想要揭开智淑的真实身份的人与已经知道所有秘密的人，这四人共同住在同一间宅邸里所发生的明争暗斗、阴谋报复的故事 。
根据古典小说记载，世上有人有妖，妖会与人相恋，妖寿命千万年，人的寿命有限，人死了，妖活着。人会投胎转世，但投胎以后，不记得上辈子的爱。妖如果痴情的话，就去找狐妖“购买”一项服务，让投胎转世的人，回忆起前世的爱。狐妖红娘这一个角色就这样诞生，作品主要讲述了以红娘为职业的狐妖在为前世恋人牵红线过程当中发生的一系列有趣、神秘的故事。
《新霹雳游侠》他是1982年至1986年在NBC播出的热门剧《霹雳游侠》的续集。 老版中，David Hasselhoff扮演的游侠驾驶着人工智跑车KITT惩恶扬善，让80年代的电视迷记忆深刻，如今游侠的儿子Mike Traceur将带领他的朋友和全新的奈特工业3000号跑车重回荧屏，继续与邪恶作斗争。
屡创收视神话的人气编剧徐英真、影视界的黑马导演李庆民、韩国当代最上镜女星吴升雅、带出过大批明星的经纪人张基俊，因为拍一部既非浪漫的灰姑娘童话、又非大赚泪水的绝症故事的电视剧“精神病也无所谓”而走到了一起。他们当中，徐英真个性张扬，吴升雅比起来也毫不逊色，而李庆民第一次执导，张基俊则对演员特有人情味儿……除了四人之外，还有众多的剧组人员，在韩剧边拍边播的体制下，他们制作的电视剧会顺利吗？其间会发生什么样的故事？
又不知敌人如何行动，一切均需临机应变。
