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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 ~The park makes full use of flowers and plants, trees, water bodies, architectural sketches, terrain treatment and other garden construction elements, and adopts the gardening method of combining natural style and planning style, overlapping mountains and managing water, integrating the characteristics of the times and traditional connotation, and creating a garden landscape with elegant and unique style. In particular, plant landscaping is used. Erythrina, a symbol of Quanzhou, a famous historical and cultural city, is used as the backbone tree species in the park, supplemented by banyan, mango, basin frame wood and other tree species. Arbor, shrub, flowers and plants are integrated into a whole to achieve the artistic effect of plant landscaping through rich spatial levels and colors. In spring, the Erythrina flower, which is shimmering like a cloud, blooms with a warm and fiery smile. It is very beautiful and makes people forget to return.彩儿笑道：小姐就放心好，小少爷吃的好。During the short one-day interview, Tashi's heart changed subtly.饷钱？这跟杨长帆有关系么？杨长帆是皇帝么？杨长帆这边也皱眉道：我先前缴过一个月的，刚刚过了十天吧？那是二月，明儿就是三月啦。沈氏家族掌门人沈正山为人沉着果断，心狠手辣，一切以利益为大前担提，即使是亲人朋友也不留情面，由其继室李燕所生的儿子沈家伟不但继承了正山在商场上的狠辣个性，加上被正山宠爱有加，性格更是好强骄纵，自视甚高，目中无人。区信安与妻子何秀莲原本是沈正山的司机和女佣，因其子区仲文的前途，而举家迁往上海。一次偶然机会，仲文与家伟相遇，两人因商场之争而发生冲突。家伟其姐沈家敏为排挤家伟不惜动用被炒员工用炸弹向家伟阿信、小树、Michael是一群喜爱摇滚的青年，初出道时，他们组团在PUB驻唱，遇流氓调戏欺负，个性火爆的阿信为保护小树，与他们大打而闹上警局，吉他手、键盘手和贝斯手相继离去，乐团被迫解散。为了生计，主唱阿信去夜市叫卖衣服，Michael也往自己的飞行梦迈进，小树则回到温泉旅馆帮忙。晓华和Tomi是香港人，为了追求音乐理想来到台北打拼，现实迫使他们只能窝在酒廊里弹"那卡西"，吃着酒廊里的残羹为生，赚来的俸禄都花在租录音室，制作创作DEMO上，甚至缴不起房租。一场救急的演出，让晓华与Tomi认识了阿信叁人。Chris出身书香世家，从小沉浸于古典音乐的优雅中，然而组团搞摇滚一直是他的梦想，就在他即将赴纽约朱莉亚音乐学院深造前，认识了寄卖贝斯的晓华，于是在命运的安排下，和阿信、Michael、小树、晓华、Tomi终于走到一起……