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go语言之旅书籍 go语言编程之旅 电子书
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适合儿童的英语绘本到底有哪些
《Reading A-Z 小学英语分级阅读下》百度网盘免费下载
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Reading A-Z 小学英语分级阅读下简介:本课程涉及“城市、动物、节日、故事、野营、生日聚会”等22个话题式分级阅读,包含约600个常用词汇,让学生通过单词、短语及句型的训练,借助场景动画,掌握“where、when、how、why”等特殊疑问词的用法,及星期、地址、天气、爱好等的表达,提升听说读的能力。
本动画片资源共22集,mp4格式超清1080p分辨率,国语发音、中文字幕,百度云网盘下载,可以在电视机或电脑、平板、IPAD、手机、车载系统等各种设备播放!适合3-8岁的小朋友观看。
Reading A-Z 小学英语分级阅读下剧集目录:
第1集 迈克今天很糟糕 Mike's Good Bad Day
第2集 母亲节 Mother’s Day
第3集 父亲节没什么事 Nothing For Father’s Day
第4集 我们的野营之旅 Our Camping Trip
第5集 警官 Police Officers
第6集 种子生长 A Seed Grows
第7集 动物骨骼 Animal Skeletons
第8集 童年故事 Childhood Stories
第9集 云 Clouds
第10集 河马牙痛 Hippo's Toothache
第11集 glooskap如何找到sum How Glooskap Found Summe
第12集 老鼠如何打败男人 How the Mice Beat the Men
第13集 稻草人 Scaredy Crow
第14集 感官 Senses
第15集 天要塌下来了 The Sky Is Falling
第16集 越来越小 Smaller and Smaller
第17集 暴风雨 The Storm
第18集 感恩节 The Thanksgiving
第19集 感恩节杰克管家 The Thanksgiving the Jacks Butler
第20集 去商店 To the Store
第21集 去树林里 To the Woods
第22集 为什么罗宾斯跳 Why Robins Hop
如何开启深度学习之旅
如何开启深度学习之旅?这三大类125篇论文为你导航(附资源下载)
如果你现在还是个深度学习的新手,那么你问的第一个问题可能是「我应该从哪篇文章开始读呢?在 G上,s准备了一套深度学习阅读清单,而且这份清单在随时更新。
项目地址:
这份清单依照下述 4 条原则建立:
从整体轮廓到细节
从过去到当代
从一般到具体领域
聚焦当下最先进技术
你会发现很多非常新但很值得一读的论文。这份清单我会持续更新。
1、深度学习的历史与基础知识
1.0 书籍
[0] Bengio, Yoshua, Ian J. Goodfellow, and Aaron Courville. 深度学习(Deep learning), An MIT Press book. (2015). (这是深度学习领域的圣经,你可以在读此书的同时阅读下面的论文)。
1.1 调查类:
[1] LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton. 深度学习 (Deep learning), Nature 521.7553 (2015): 436-444. (深度学习三位大牛对各种学习模型的评价)
1.2 深度信念网络(DBN)(深度学习前夜的里程碑)
[2] Hinton, Geoffrey E., Simon Osindero, and Yee-Whye Teh. 一个关于深度信念网络的快速学习算法(A fast learning algorithm for deep belief nets), (深度学习的前夜)
[3] Hinton, Geoffrey E., and Ruslan R. Salakhutdinov. 使用神经网络降低数据的维度(Reducing the dimensionality of data with neural networks), (里程碑式的论文,展示了深度学习的可靠性)
1.3 ImageNet 的演化(深度学习从这里开始)
[4] Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. 使用深度卷积神经网络进行 ImageNet 分类任务(Imagenet classification with deep convolutional neural networks)(AlexNet, 深度学习的突破)
[5] Simonyan, Karen, and Andrew Zisserman. 针对大尺度图像识别工作的的超深卷积网络(Very deep convolutional networks for large-scale image recognition) (VGGNet, 神经网络开始变得非常深!)
[6] Szegedy, Christian, et al. 更深的卷积(Going deeper with convolutions)(GoogLeNet)
[7] He, Kaiming, et al. 图像识别的深度残差学习(Deep residual learning for image recognition)(ResNet,超级超级深的深度网络!CVPR--IEEE 国际计算机视觉与模式识别会议-- 最佳论文)
1.4 语音识别的演化
[8] Hinton, Geoffrey, et al. 语音识别中深度神经网络的声学建模(Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups)(语音识别中的突破)
[9] Graves, Alex, Abdel-rahman Mohamed, and Geoffrey Hinton. 用深度循环神经网络进行语音识别(Speech recognition with deep recurrent neural networks)(RNN)
[10] Graves, Alex, and Navdeep Jaitly. 面向端到端语音识别的循环神经网络(Towards End-To-End Speech Recognition with Recurrent Neural Networks)
[11] Sak, Ha?im, et al. 语音识别中快且精准的循环神经网络声学模型(Fast and accurate recurrent neural network acoustic models for speech recognition)(语音识别系统)
[12] Amodei, Dario, et al. Deep speech 2:英语和汉语的端到端语音识别(Deep speech 2: End-to-end speech recognition in english and mandarin)(百度语音识别系统)
[13] W. Xiong, J. Droppo, X. Huang, F. Seide, M. Seltzer, A. Stolcke, D. Yu, G. Zweig,在对话语音识别中实现人类平等(Achieving Human Parity in Conversational Speech Recognition)
当你读完了上面给出的论文,你会对深度学习历史有一个基本的了解,深度学习建模的基本架构(包括了 CNN,RNN,LSTM)以及深度学习如何可以被应用于图像和语音识别问题。下面的论文会让你对深度学习方法,不同应用领域中的深度学习技术和其局限有深度认识。
2 深度学习方法
2.1 模型
[14] Hinton, Geoffrey E., et al. 通过避免特征检测器的共适应来改善神经网络(Improving neural networks by preventing co-adaptation of feature detectors)(Dropout)
[15] Srivastava, Nitish, et al. Dropout:一种避免神经网络过度拟合的简单方法(Dropout: a simple way to prevent neural networks from overfitting)
[16] Ioffe, Sergey, and Christian Szegedy. Batch normalization:通过减少内部协变量加速深度网络训练(Batch normalization: Accelerating deep network training by reducing internal covariate shift)(2015 年一篇杰出论文)
[17] Ba, Jimmy Lei, Jamie Ryan Kiros, and Geoffrey E. Hinton.层归一化(Layer normalization)(批归一化的升级版)
[18] Courbariaux, Matthieu, et al. 二值神经网络:训练神经网络的权重和激活约束到正 1 或者负 1(Binarized Neural Networks: Training Neural Networks with Weights and Activations Constrained to+ 1 or?1)(新模型,快)
[19] Jaderberg, Max, et al. 使用合成梯度的解耦神经接口(Decoupled neural interfaces using synthetic gradients)(训练方法的发明,令人惊叹的文章)
[20] Chen, Tianqi, Ian Goodfellow, and Jonathon Shlens. Net2net:通过知识迁移加速学习(Net2net: Accelerating learning via knowledge transfer) (修改之前的训练网络以减少训练)
[21] Wei, Tao, et al. 网络形态(Network Morphism)(修改之前的训练网络以减少训练 epoch)
2.2 优化
[22] Sutskever, Ilya, et al. 有关深度学习中初始化与动量因子的研究(On the importance of initialization and momentum in deep learning) (动量因子优化器)
[23] Kingma, Diederik, and Jimmy Ba. Adam:随机优化的一种方法(Adam: A method for stochastic optimization)(可能是现在用的最多的一种方法)
[24] Andrychowicz, Marcin, et al. 通过梯度下降学习梯度下降(Learning to learn by gradient descent by gradient descent) (神经优化器,令人称奇的工作)
[25] Han, Song, Huizi Mao, and William J. Dally. 深度压缩:通过剪枝、量子化训练和霍夫曼代码压缩深度神经网络(Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding) (ICLR 最佳论文,来自 DeePhi 科技初创公司,加速 NN 运行的新方向)
[26] Iandola, Forrest N., et al. SqueezeNet:带有 50x 更少参数和小于 1MB 模型大小的 AlexNet-层级精确度(SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and 1MB model size.) (优化 NN 的另一个新方向,来自 DeePhi 科技初创公司)
2.3 无监督学习/深度生成模型
[27] Le, Quoc V. 通过大规模无监督学习构建高级特征(Building high-level features using large scale unsupervised learning.) (里程碑,吴恩达,谷歌大脑,猫)
[28] Kingma, Diederik P., and Max Welling. 自动编码变异贝叶斯(Auto-encoding variational bayes.) (VAE)
[29] Goodfellow, Ian, et al. 生成对抗网络(Generative adversarial nets.)(GAN, 超酷的想法)
[30] Radford, Alec, Luke Metz, and Soumith Chintala. 带有深度卷曲生成对抗网络的无监督特征学习(Unsupervised representation learning with deep convolutional generative adversarial networks.)(DCGAN)
[31] Gregor, Karol, et al. DRAW:一个用于图像生成的循环神经网络(DRAW: A recurrent neural network for image generation.) (值得注意的 VAE,杰出的工作)
[32] Oord, Aaron van den, Nal Kalchbrenner, and Koray Kavukcuoglu. 像素循环神经网络(Pixel recurrent neural networks.)(像素 RNN)
[33] Oord, Aaron van den, et al. 使用像素 CNN 解码器有条件地生成图像(Conditional image generation with PixelCNN decoders.) (像素 CNN)
2.4 RNN/序列到序列模型
[34] Graves, Alex. 带有循环神经网络的生成序列(Generating sequences with recurrent neural networks.)(LSTM, 非常好的生成结果,展示了 RNN 的力量)
[35] Cho, Kyunghyun, et al. 使用 RNN 编码器-解码器学习词组表征用于统计机器翻译(Learning phrase representations using RNN encoder-decoder for statistical machine translation.) (第一个序列到序列论文)
[36] Sutskever, Ilya, Oriol Vinyals, and Quoc V. Le. 运用神经网路的序列到序列学习(Sequence to sequence learning with neural networks.」)(杰出的工作)
[37] Bahdanau, Dzmitry, KyungHyun Cho, and Yoshua Bengio. 通过共同学习来匹配和翻译神经机器翻译(Neural Machine Translation by Jointly Learning to Align and Translate.)
[38] Vinyals, Oriol, and Quoc Le. 一个神经对话模型(A neural conversational model.)(聊天机器人上的序列到序列)
2.5 神经图灵机
[39] Graves, Alex, Greg Wayne, and Ivo Danihelka. 神经图灵机器(Neural turing machines.)arXiv preprint arXiv:1410.5401 (2014). (未来计算机的基本原型)
[40] Zaremba, Wojciech, and Ilya Sutskever. 强化学习神经图灵机(Reinforcement learning neural Turing machines.)
[41] Weston, Jason, Sumit Chopra, and Antoine Bordes. 记忆网络(Memory networks.)
[42] Sukhbaatar, Sainbayar, Jason Weston, and Rob Fergus. 端到端记忆网络(End-to-end memory networks.)
[43] Vinyals, Oriol, Meire Fortunato, and Navdeep Jaitly. 指示器网络(Pointer networks.)
[44] Graves, Alex, et al. 使用带有动力外部内存的神经网络的混合计算(Hybrid computing using a neural network with dynamic external memory.)(里程碑,结合上述论文的思想)
2.6 深度强化学习
[45] Mnih, Volodymyr, et al. 使用深度强化学习玩 atari 游戏(Playing atari with deep reinforcement learning.) (第一篇以深度强化学习命名的论文)
[46] Mnih, Volodymyr, et al. 通过深度强化学习达到人类水准的控制(Human-level control through deep reinforcement learning.) (里程碑)
[47] Wang, Ziyu, Nando de Freitas, and Marc Lanctot. 用于深度强化学习的决斗网络架构(Dueling network architectures for deep reinforcement learning.) (ICLR 最佳论文,伟大的想法 )
[48] Mnih, Volodymyr, et al. 用于深度强化学习的异步方法(Asynchronous methods for deep reinforcement learning.) (当前最先进的方法)
[49] Lillicrap, Timothy P., et al. 运用深度强化学习进行持续控制(Continuous control with deep reinforcement learning.) (DDPG)
[50] Gu, Shixiang, et al. 带有模型加速的持续深层 Q-学习(Continuous Deep Q-Learning with Model-based Acceleration.)
[51] Schulman, John, et al. 信赖域策略优化(Trust region policy optimization.) (TRPO)
[52] Silver, David, et al. 使用深度神经网络和树搜索掌握围棋游戏(Mastering the game of Go with deep neural networks and tree search.) (阿尔法狗)
2.7 深度迁移学习/终身学习/尤其对于 RL
[53] Bengio, Yoshua. 表征无监督和迁移学习的深度学习(Deep Learning of Representations for Unsupervised and Transfer Learning.) (一个教程)
[54] Silver, Daniel L., Qiang Yang, and Lianghao Li. 终身机器学习系统:超越学习算法(Lifelong Machine Learning Systems: Beyond Learning Algorithms.) (一个关于终生学习的简要讨论)
[55] Hinton, Geoffrey, Oriol Vinyals, and Jeff Dean. 提取神经网络中的知识(Distilling the knowledge in a neural network.) (教父的工作)
[56] Rusu, Andrei A., et al. 策略提取(Policy distillation.) (RL 领域)
[57] Parisotto, Emilio, Jimmy Lei Ba, and Ruslan Salakhutdinov. 演员模仿:深度多任务和迁移强化学习(Actor-mimic: Deep multitask and transfer reinforcement learning.) (RL 领域)
[58] Rusu, Andrei A., et al. 渐进神经网络(Progressive neural networks.)(杰出的工作,一项全新的工作)
2.8 一次性深度学习
[59] Lake, Brenden M., Ruslan Salakhutdinov, and Joshua B. Tenenbaum. 通过概率程序归纳达到人类水准的概念学习(Human-level concept learning through probabilistic program induction.)(不是深度学习,但是值得阅读)
[60] Koch, Gregory, Richard Zemel, and Ruslan Salakhutdinov. 用于一次图像识别的孪生神经网络(Siamese Neural Networks for One-shot Image Recognition.)
[61] Santoro, Adam, et al. 用记忆增强神经网络进行一次性学习(One-shot Learning with Memory-Augmented Neural Networks ) (一个一次性学习的基本步骤)
[62] Vinyals, Oriol, et al. 用于一次性学习的匹配网络(Matching Networks for One Shot Learning.)
[63] Hariharan, Bharath, and Ross Girshick. 少量视觉物体识别(Low-shot visual object recognition.)(走向大数据的一步)
3 应用
3.1 NLP(自然语言处理)
[1] Antoine Bordes, et al. 开放文本语义分析的词和意义表征的联合学习(Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing.)
[2] Mikolov, et al. 词和短语及其组合性的分布式表征(Distributed representations of words and phrases and their compositionality.) (word2vec)
[3] Sutskever, et al. 运用神经网络的序列到序列学习(Sequence to sequence learning with neural networks.)
[4] Ankit Kumar, et al. 问我一切:动态记忆网络用于自然语言处理(Ask Me Anything: Dynamic Memory Networks for Natural Language Processing.)
[5] Yoon Kim, et al. 角色意识的神经语言模型(Character-Aware Neural Language Models.)
[6] Jason Weston, et al. 走向人工智能-完成问题回答:一组前提玩具任务(Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks.) (bAbI 任务)
[7] Karl Moritz Hermann, et al. 教机器阅读和理解(Teaching Machines to Read and Comprehend.)(CNN/每日邮件完形风格问题)
[8] Alexis Conneau, et al. 非常深度卷曲网络用于自然语言处理(Very Deep Convolutional Networks for Natural Language Processing.) (在文本分类中当前最好的)
[9] Armand Joulin, et al. 诡计包用于有效文本分类(Bag of Tricks for Efficient Text Classification.)(比最好的差一点,但快很多)
本兮的资料,飞轮海的,还有陶喆的
飞轮海资料
本名:汪东成
生日:1981/8/24
星座:处女座
学历:复兴美工"广设科"
身高:"180"
演出经历:
☆☆ MTV☆☆
MAKIYO"还给你"MTV
张惠妹"记得"MTV (带头巾搬货的那个)
梁静如"分手快乐"合唱版
☆☆CF☆☆
多喝水cf"躺在浴缸篇"
有氏没氏非常茶饮料
来一客泡面"甩尾篇"
台新银行u be卡"日本泡汤篇"
MOTOROLA好礼大方送"taxi篇"
立顿奶茶"破了比较好篇"
新光人寿"美丽人生篇"
爱之味鲜采蕃茄汁"保时捷篇"
☆☆平面☆☆
"木野直人村明秀"服装代言人...已经当了三季喔!
ps在很多百货公司都可以看得到,譬如:sogo,京华城,依蝶,西门诚品等...
☆☆ 戏剧☆☆
偶像剧"听笨金鱼唱歌"
偶像剧"恶作剧之吻"
偶像剧"终极一班"
本名:辰亦儒
小名::陈奕儒
英文名:Calvin (基本上朋友都这么叫我)
身高:184 cm
体重:65 kg
生日:1980/11/10
星座:天蝎座
学历:建中 温哥华Simon Fraser University 大学 主修经济维多利亚 University of Victoria 硕士 主修经济
血型: A型
鞋号:US 10.5 号
三围: 37, 31, 36
家庭成员:爸爸 妈妈 一个姐姐
喜欢的颜色:蓝色 白色
兴趣:健身 网球 唱歌
个性: 风趣幽默
专长: 反应很快 嘿嘿
歌声如何: 还不赖 自认中上 哈 眞的啦 录音师也这么说^^
近视:小时是电视儿童 所以 两眼都550 @@
头发:微卷 以前超不爱 超限慕直发的人 但后来发现卷发其实好做造型 也不赖 哈
口头禅:没啥特别的口头禅ㄟ
英文能力:国外研究所的能力搂
拍过的MV:拍摄当届创作歌曲选拔冠军"难以抗拒" 的音乐录影带
拍过的广告:一堆加拿大温哥华阳光男孩公益活动的广告 大概有5支左右吧
欣赏的女生类型:气质型
家人对calvin进演艺圈的看法:书读了那么多 给我跑去演艺圈 贞士气死人 哈 所以我需要你们的大力只持 交出好成绩给爸妈看 证明给他们看!!
平常喜欢:跟好友聚在一起 做什么都可以 因为我很重视友谊
喜欢电影种类:好看的话 不管是动作 喜剧 文艺爱情 惊悚 我都爱
最爱的电影:很多ㄟ 不过我很喜欢 妮可拉斯凯吉演的任何电影 他的演技真是没话说
喜欢的歌手: 不如说是音乐种类吧 Hip Pop and RB
喜欢的女演员:
喜欢的男演员:梁朝伟 吴镇宇
喜欢的日本艺人:木村 帅
喜欢的漫画:男生爱看的 譬如 七龙珠 灌篮高手 神型太保
喜欢看哪类型的小说:
最想去的国家:加拿大 像是我第2个家 毕竟我呆了7年 我很想环游世界 喜欢不同的文化
喜欢的音乐类型:Hip Pop and RB
喜欢什么动物: 狗 超爱 之前加拿大养了两只比熊 不知道你们只不知道这个品种 有点像马尔季斯 但比马尔季斯大一点
喜欢的食物:Japanese Food and Western food..Junk food..哈
喜欢看书或上书店:以前在国外认为在书店喝咖啡看书是种享受 很爱忙裏偷闲的感觉 嘿
喜欢购物:超爱 基本上 我逛街可超像女生 哈 跟我逛街的男生都很受不了 觉得我超会逛
害怕什么事物: 害怕的事还好 但不喜欢伤心的事 譬如失恋 或跟朋友吵架这类的
平常的穿衣style:两极化 有时很休闲 有时爱穿很正式耍帅 哈
印象最深刻的事:7年前一个人独自上加拿大生活 一直一个人过了7年
接过哪一件最辛苦的CASE:还好ㄟ 不过夏天拍戏 真是热热热
希望能和所有的Fans共同做什么事:多点见面会 多认识你们 我会好好努力记住你们的名字 你们只要见到我 我较不出你的名字 就再提醒我一次 直到我记住为止 哈 基本上我记性很好的喔
当艺人前从事过什么工作: 都在加拿大念书 念研究所当过学校大学助教
喜欢哪一类的书:
初恋和初吻几岁:16岁 高一
谈过几次恋爱:好私人喔 不过不多啦 真的 5次以下 可以了吧 哈
讨厌什么样的人:就是两面人搂
讨厌什么昆虫或动物:
最糗的事:
最痛苦的事:
梦想: 演艺圈闯出一番好成绩 这是我目前最大的愿望吧
对未来的期望:
calvin名言: Shakespear says: To be or not to be, that's a question..ha ha
本名:吴庚霖
艺名:炎亚纶
匿称:阿布
生日:1985/11/20
星座:天蝎座
血型:O
身高:177
体重:60
学历:文化大学新闻系
语言:国语、英语
嗜好:篮球、跳舞、唱歌、交朋友、爱搞怪
个性:多变 但大部分是话少却好相处
三围:胸围忘ㄌ 28 36
身体状况:轻微气?
专长:钢琴长笛 篮球
最喜欢的团体:信乐团
最喜欢的男演员:刘德华
最喜欢的女演员:林依晨
最喜欢的男歌手:哈林、林俊杰
最喜欢的女歌手:林凡、梁静茹
最想去的国家:都想去^^
最喜欢的音乐类型:soul rock pop RB hard rock jaz
最喜欢什么东西?有心意ㄉ东西
最喜欢的颜色:绿色蓝色黄色黑色
欣赏的女生类型:个性比较重要罗
让你印象最难忘的事:初恋的心碎...
最糗的事:ㄟ...怎么会有糗事发生在我身上勒
谈过几次恋爱?哈哈蛮多次ㄉ
梦想:现在正在走ㄉ未来将达成ㄉ就是我ㄉ梦想
想对家族成员说的话:你们每ㄍ人都很贴心也很可爱 我们要一起加油 考上大学...(不是啦) 你们每ㄍ人都要好好照顾身体 一定每天都要健健康康!! 真ㄉ!! 不管到哪裏心都与你们相系
寄东西给你要寄到哪? 110 台北市信义区嘉兴街311号三楼 炎亚纶收
§演艺经历:
戏剧-
2004 安室爱美惠
2005 恶作剧之吻
2005 终极一班
团体-
2005 飞轮海
比赛-
2004 新光三越第二届阳光男孩选拔台北区(初赛)
姓名:吴尊
生 日 1980/10 /10
身 高 182 cm
体 重 73 kg
鞋 号 10 号
胸 围 40
腰 围 31
臀 围 38
故 乡 汶 莱
学校:RMIT大学,澳洲(RMIT UNIVERSITY, AUSTRALIA (BACHELOR OF BUSINESS IN BUSINESS ADMINISTRATION)
个性:害羞,见忘,事业为重。
嗜好: 打篮球,健身,看书,听音乐,看电影,吃,煮饭和旅行。
喜欢的颜色:看情况…
喜欢的食物: 我很爱吃,除了油腻的食物我甚么都吃。
喜欢的饮料:无酒精的鸡尾酒饮料 MOCKTAIL
喜欢的音乐: 看心情
喜欢的地方: 纽约
最想去的城市: 纽约
喜欢的电影: 英雄本色
最喜欢的季节: 春
喜欢的卡通人物: 超人
最喜欢的花/花语:百合
几岁初恋:16岁
喜欢异性类型: 对我而言,最重要的昰感觉。
最讨厌的事情:失去我身边最重要的人
最大的愿望: 在生命里做个好与事业有成的人
做过最难忘的事情: 在照顾去世前的妈妈
做过最后悔的事情: 在妈妈去世前没花足够的时间在她的身边
做过最有勇气的事情: 在台湾继续追求我在演艺圈的事业
吴 尊 在 汶 莱 时 是 健 身 教 练
以 前 为 伊 林 的 模 特 儿 , 现 为 飞 轮 海 团 员 之 一
本兮的资料
90后优秀网络歌手 【姓名历程】 2009年6月30日本兮vce改名为Utaoki。
剪了短发的zzyo。
[1]2009年8月26日Utaoki改名为执子右zzyo。 2010年4月又改回本兮(不是什么Vce,只是本兮) 真实姓名:马晓晨 性别:女 生日:1994年6月30日 星座:巨蟹座 职业:学生、网络歌手 籍贯:新疆奎屯市(目前就读于上海某学校) 歌曲风格:大多都是说唱RAP和POP,也有甜蜜风的歌曲(如:爱你那么多、甜蜜full in love 等) 唯一百度贴吧:本兮吧 唯一歪歪ID:51690 原创歌曲:1.失恋别在意 2.甜蜜full in love(本兮K-len) 3.回忆(本兮feel) 4.路还要走(本兮 小右 RST) 5.终点(RST 本兮 孙小俊) 6.冷水 香水(本兮鱼圏) 7.送给我的朋友们 8.情人节的夜晚(本兮小贱) 9.樱花般的爱(本兮欧阳正萌) 10.支离破碎(本兮jong) 11.不是分开就不再(本兮BOBO) 12.爱你那么多(甜蜜风) 13.Dance with Ya(本兮iMoNi ft.C蓝) 14.哎 小3 你好贱 15.过眼飘散(本兮小伟) 16.曲终人未散 17.送给一些无聊的人 18.温存 19.她 20.纪念 21.纪念 新版
本兮
[2]22.一首歌 倾诉所有 23.让我为你唱首歌 24.你不会懂 25.情不至 26.想陪你一起旅行 27.想陪你一起旅行(完结) 28.柒末雪 29.情已逝去 30.待续 31.I wanna be your friend 32.最后的最后 33.戒 34.再见 baby 35.怎么办 我爱你 36.怎么办 我想你(两首送给ecbe的歌,空间外链火爆) 37.buried our love 38.之后 39.对不起 宝贝 40.累了 41.樱花的眼泪 42.寸断 43.海誓山盟亦会分开 44.爱情电影 45.心灵深处 46.属于我们的歌 47.很无奈的歌 48.在悲伤之后 49.sexy time 50.弹情 51.到底该 52.掩饰 53.再见 禸场梦 54.每天 我拿着笔 55.阿呸.本兮 56.
本兮原来的样子哦。
很sweet 57.最sweet 58.diss淋儿 (给vEra淋児的歌她盗本兮20多首歌) 59.diss淋儿again 60.diss 戴雨诺(同样是盗本兮的歌) 翻唱歌曲: 毒 卑恋 桥段 river flows in you 多余的解释 你若成风 夏天的风 单曲循环 起义之日 爱你卡农 差不多先生 园游会 山盟海誓亦会分开 洋娃娃和小熊跳舞 哈里路亚 一分一秒 Nobody Best friend
出生地:香港 童年居住地:台湾台北 父亲祖籍地:江苏南京 母亲祖籍地:
陶喆的资料
演唱会照(14张)上海 宗教信仰:基督教 生肖:鸡 血型:O型 星座:巨蟹座 学历:台北公馆伯大尼美国学校,UCI,UCLA毕业,读过AFI 主修:心理学,电影 语言:国语,英语,西班牙语,闽南语等 性格:富有创意,主观性强,完美主义者,神经质,性感 最爱:艺术,汽车,电影,音乐 喜欢:美食 讨厌:电子游戏,棋类游戏
陶喆 专辑封面(15张)喜欢的书籍杂志:学术性,艺术,汽车,烹饪,现代著作,文化,时装,健康, 电影,音乐,真实故事,心灵自疗,旅游,计算机科技,西方名著 最喜爱的作家,书籍,杂志:Harry Potter Series 喜欢的音乐:另类音乐,Big-Band,蓝调音乐,Calypso,中国民间音乐,中国戏曲,古典音乐,古典摇滚,乡村音乐,二胡音乐,实验音乐,民谣,Funk,福音歌曲,新古典歌特音乐,重金属电子摇滚,工业音乐,爵士乐,新摇滚,新世纪音乐,流行乐,Rap,Reggae,乡村摇滚,Salsa,爵士灵歌,电影配乐,颂歌,强节奏爵士乐,多类型音乐,世界音乐,电子音乐 喜爱的歌手,乐队:John Lennon,Beatles,Sting,罗大佑 喜欢的电影:艺术片,动作片,喜剧,纪录片,恐怖片,爱情片,科幻片,悬疑片,动画 最喜爱的导演,演员,电影:Taxi Driver ,Annie Hall,Steven Spielberg ,Woody Allen 喜欢的运动:田径,健身,远足,滑冰,武术,越野单车,赛车,单车,跑步,缓步跑,壁球,游泳,乒乓球,排球,散步,举重 喜欢的宠物:狗,鱼,仓鼠,蜥蜴,蛇,龟,猫 一句最重要的话:喝酒我爱保持清醒,吸烟我不想危害健康。
英语演讲稿读书五篇
打开一本书,就好像轻轻感受到淳淳杨柳风,扑面而来;就好像慢慢感受到蒙蒙杏花雨,从天而降;就似乎全新体验到浩浩竹林带给你的轻松与快感。一起来看看 英语 演讲稿 读书五篇,欢迎查阅!
英语演讲稿读书1
What is a great book? There is no end to the making of books. Nor does there seem to be any end to the making lists of great books. There has always be more books than one could read. You can be happy at the fact that the number of that is relatively small.
However,today,people usually leave it in the library. According to the national reading survey issued by The China Academy of Press and Publication, in 2012, only 55% Chinese aged between18 and 70 book read books .That is to say, there are more than forty percent of the people seldom read in China.
It is a great challenge to literature. As a educated student,have you insist on reading great books. In order to change the situation ,we must take actions to read great books.
In Adler’s essay of What is A Great Book, he explain why we should read great books. I conclude it as follows.
First,great books are the most readable. They will not let you down ,if you read them well. The have more ideas per page than most books in the their entirety. This is why you can read a great book over and over again and never exhaust it contents.
Second ,great books are always contemporary,in contrast to the books we called contemporary,because they are currently popular ,last for a year or tow,or ten at most. You may probably can not recall the names of many earlier best sellers,and you may probably would not be interest in reading them. But the great are never out modeled by the movement of thought or the shifting winds of opinion .
Third ,great books are the most instructive. This follows the fact that they are original communications. They contain what cannot be found in other books. Whether you ultimately agree or disagree what they say. They are the primary teachers of mankind. They have made basic contribution to human right .
Just giving you the reason is not enough, I will give you some methods to realize you reading dream.
Firstly,you can begin with a interesting novel. You will be attracted by the figures,the plots .Than ,after reading a lot of books ,you may be get into a habit of reading. So,you can contact with some complex books,such as philosophy ,arts and so on. You will be shocked at the new world.
There are countless great books in our library,you must make great advantage of it. Of course ,it is a better choice to buy great books. Collecting books is a enjoyable thing,at least for me. So,reading great books. The new world is coming.
英语演讲稿读书2
good morning ladies and gentlemen. today i’m very glad to be here with you to share my stories and opinions about reading. i love reading from the bottom of my heart. and i do learn a lot from books. i know the wonderful stories of great heroes in history, secrets of nature, mysteries of ufo and our universe. to me , books are like a faithful friend, always around me , giving me enjoyment and wisdom. i remember when i was in primary school, ten or eleven years old, my father borrowed some books from the library in his school. those were among the greatest works of the world, including abrabian nights、the legend of deification, journey to the west, and the romance of the three kingdoms. these books were all written in
ancient chinese characters but i tried to read the heavy books and were deeply attracted. from then on, i spared every minute to read whatever i could get. whenever i got a new book, i kept reading until i finished it despite time and place. i read books even in class or just a few minutes before the exams. in my mind, there is always an unforgettable scene: lying in bed, nervous but excited, my friend and i read a book together in the weak light of a flashlight , with a quilt on us, in order not to be blamed by parents. all my classmates thought i was crazy and gave me a nickname “bookworm”. so you can understand why i got my eyes shortsighted.
till now, i still like reading as i used to. and i’m very
pleased to see that my ten-year-old son loves reading just like me. i have bought him many books. whenever you come into my home, you can find books in every corner. but the place where my son and i enjoy reading most is in the toilet. so it often happens in the morning: one is in the toilet reading something comfortably, while another
walking outside , shouting. for my age, i like to read magazines or short stories to get relaxation as well as inspiration.
today we live in a world of prosperity. never before have we
faced so many temptation from the outside world. never before have we had so many chances to enjoy our lives. we drive rather than walking; we go online to chat with people we’ve never met before instead of talking to friends around us. but there’s always something that cannot be replaced and forgotten., such as books. so i will allow myself to continue the journey in the ocean of books until the very end of my life.
finally, i’d like to end my speech with a great philosopher, writer and thinker, francis bacon’s famous saying: reading makes a full man. studies serve for delight, for ornament, and for ability. thank you very much.
女士们,先生们,早上好。今天我很高兴在这里与你分享我的 故事 ,关于阅读意见。我喜欢阅读从我的心底。而我也从书本中学习很多。我知道在历史上伟大的英雄,自然秘密,我们的宇宙奥秘和不明飞行物的精彩故事。对我来说,书像一个忠实的朋友,总是围绕着我,给我的享受和智慧。
我记得当我在小学,10或11岁的时候,我父亲在他借用了学校图书馆的书籍。这些都是在世界最伟大的.作品,包括abrabian夜,在神化, 传说 西方之旅,和三国演义。这些书都是写在古老的汉字,但我试图读出沉重的书籍,被深深吸引。从此,我每分钟的时间读完不遗余力我能得到什么。每当我得到一本新书,我一直在读书,直到我完成了,尽管它的时间和地点。甚至在课堂上我读到或只是在考试前几分钟的书籍。在我心目中,始终有一个令人难忘的一幕:在床上,紧张而兴奋,我的朋友说谎,我读了书一起在手电筒微弱的光与我们的被子上,为了不被父母责备。我所有的同学以为我疯了,给了我一个绰号“书呆子”。所以你可以理解为什么我得到了我的眼睛近视。
英语演讲稿读书3
Which Is More Important: Knowledge from Books or
Knowledge from Experience
As we know, most knowledge we have comes from two sources: the books or personal experience in our daily life. Each one has its advantage. Maybe some people think that book knowledge is more important than experience knowledge. However, I am strongly against their opinion. I consider that experience is more useful.
Firstly, practical experience can help us find jobs successful. There are two kinds of people: experienced employees and college graduates, if you are a manager, which one do you prefer? There is no doubt that you will choose the experienced employees. Because they have more practical knowledge, they understand what their companies needs and how to make profit for their companies. Some college graduates have learned much book knowledge, but they can’t take advantage of these theories effectively. Therefore, many companies are not willing to employ graduates. This phenomenon tells us experience is more important for us to find good jobs.
Secondly, experience can give us more impressed knowledge. It’s said that one learn by doing, if you want to make advances, it’s necessary to practice. Moreover, we learn how to get along with others or how to have self-respect from experience. We feel happy and sorrow directly from experience. The precious knowledge absolutely can’t get from books.
Thirdly, our country’s development depends on innovation, which comes from experimentation. Comparing Chinese education system with American’s, we know that Chinese education usually pay more attention to scores students get and neglect their ability of innovation. On the contrary, American education emphasizes personal practice, that’s the reason why the progress of American technology is so rapid. The contrast reminds us of the importance of experience knowledge.
Needless to say both learning sources have their own advantages. But in my opinion, experience knowledge is more important, because without practical experience, it’s impossible to get a real understanding of book knowledge, and to know how to apply this knowledge to real situations.
英语演讲稿读书4
Everyone have dreams, which are everybody yearning. The man who without dreams
每个人都有梦想, 它是人人所渴望的。 没有梦想的人
in his life will be empty, but dreams always be changing as your thought go forward.
的人生将是空白的, 但梦想总是随着你思想的前进而改变的。
When I was in primary school, I had a dream. I hope that I won't have homework 当我小学时, 我有一个梦想。我希望将来有一天可以没有有家庭作业。 to do one day. But the time we can play have became less and less, and 1/3 in our 可玩耍的时间变得越来越少, 而我们一天中的三分之一 day we were imprisoned in the classroom, so many time on study! And till I come 被禁锢在教室, 太多时间在学习上。 直到我上 to the junior high school, I had a dream, I hope I can become a good child,I can 初中 我有一个梦想,我希望自己能成为一个好孩子;
be praised by my family when I return home;can be sure by teachers at school; and 回到家能受到家人的表扬; 在学校能受到老师们的肯定;
can have a outstanding performance among the classmates .So shortly afterwards, ;在同学之间能有出众的表现。 所以不久后,
I had learned to struggle. However, at my high school, every day is bustling, 我学会了奋斗。 然而, 上了高中后, 每天都是忙忙碌碌的, Sometimes bad temper is too strong to be controlled ,but life made me understand 有时候坏脾气是如此强烈以至于不能被控制, 但生活让我
the truth to conduct myself slowly。Fortunately, I worked hard, every day 慢慢懂得做人的道理。 幸运的是, 我会努力,每一天
I got up early and went to bed late, grasp myself and never lighten up. 我都在为了梦想而起早赶晚, 把握自己不再松散。
All day,all the time, I am searching hardly, and fight for a bright future. 每一天, 甚至每一刻 , 我都苦苦探索, 为了光明的未来而奋斗。 With the dream, chase turned up, with the goal, power turned up. Dream, is a
有了梦想,也就有了追求; 有了目标,就有了动力。 梦想,是一架 high bridge, regardless of whether it can reach the other shore。 To process dreams, 高高的桥梁,不管最终是否能到达彼岸,拥有梦想,
and to pursue them, try to make them come true ,this is a kind of success, a 并去追求它,努力使其实现, 这已经是一种成功,
kind of glory. In the process of the pursuit of dreams ,we are growing up!! 一种荣耀。 在追梦这个过程中, 我们是在成长的。
Dreams can urge people make progress endlessly, perhaps in this road ,we will 梦想会催人不断前进, 也许在这条道路中,我们将会meet many difficulties and frustrations, but never mind, Where you fall down, 遇到无数的挫折和困难, 但没关系, 在哪里跌倒
is where you should stand up, for your dream and future! After all, the future 就在哪里爬起来, 为自己的梦想和未来, 毕竟, 前途 not only rely on luck, also depend on our own.
不仅靠运气, 也靠我们自己。
Friends, let us work together! Because I believe that no pain no gain!!
朋友,让我们一起努力吧!因为我相信no pain no gain!
英语演讲稿读书5
Speaking of reading, many people are excited because reading brings them both knowledge and entertainment。 By reading, we can learn lots of information and know our history。 But for some people, reading is not their priority。 They will choose to watch movies to have fun。 However, I think people can benefit a lot by reading。
说起读书,很多人都很兴奋,读书不仅仅能带给他们知识,而且也能带给他们娱乐。透过读书,我们能得到很多信息,了解我们的历史。但是对于一部分人来说,阅读并不是他们的首选。他们会选取看电影来找乐子。但是,我认为,读书能让我们获益。
First of all, reading can let us know what have happened in history。 Since history is recorded in books, if we read books, then we can not only what have happened in history but also we can better understand the great figures of the age。
第一,读书能让我们明白历史。历史都被记录在数中,如果我们读书的话,我们不仅仅能了解历史,而且我们也能更加了解时代伟人。
Secondly, reading can enrich our knowledge。 By reading, we can know different kinds of things, how things happen and how to avoid bad things from happening。 Books record a wide range of things about life。 Through reading, we can know various aspects of life。
第二,读书能让我们丰富我们的知识。透过读书,我们能了解很多事物,了解到事件是怎样发生的,怎样避免不利事件的`发生。书本记录着社会的方方面面。透过读书,我们能了解生活的方方面面的知识。
Thirdly, reading teaches us skills。 There are so many books about how to learn a certain language, how to get a good job, how to bee popular in your circle, how to cook and so on。 Thus, these kinds of books can make us more skillful if we do a certain thing。
第三,我们能透过读书来学习一些技能。很多书都是写关于怎样学会一门语言,怎样找到一份好工作,怎样让自我在圈子中更受欢迎以及怎样烹饪等之类的东西。透过这些书,我们能在做事的时候更加熟练。
All in all, we can find lots of benefits through reading。
总之,我们能够透过读书收获很多。
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