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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 ~A3.1. 1 Medical history by set.In other words, Lv Meng causes 38 fixed damage per flat A.1) It is difficult to synchronize the production environment and the development environment, which leads to the work value of testers. It is often difficult to fully reflect the work value of testers because the environment is not synchronized. If the local development environment passes the test, problems often occur in the production environment.虽有些疑惑，但板栗也不相信有鬼，更不相信有人，只怕是什么小动物之类的。300多年前，女巫们为了保卫自己的国家与政府达成协议，结束了对女巫的迫害。《塞勒姆要塞:祖国》讲述了三位年轻女性从战斗魔法的基础训练到早期部署的故事。在这个世界上，性别和权力的传统角色发生了转变，更多的女性在前线与迫在眉睫的恐怖主义威胁作斗争，这些威胁我们这个世界并不陌生，但她们使用的是超自然的战术和武器。该剧还邀请了Ashley Nicole Williams、Jessica Sutton、Taylor Hickson、Demetria McKinney和Amalia Holm等明星加盟。《祖国:塞勒姆堡》执行制片:艾略特·劳伦斯、威尔·法瑞尔、亚当·麦凯、凯文·梅西克、玛丽亚·马根蒂和史蒂文·阿德尔森。