“Miao Fan”版本间的差异

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[https://v1.overleaf.com/read/qxjhwxwvyhfv 个人简历]
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[https://godfanmiao.gitee.io/homepage/ 个人主页]
[https://sites.google.com/view/miao-fan/home Curriculum Vitae 主页(海外版)]
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[http://weibo.com/fanmiaothu/ 新浪微博]
 
[http://weibo.com/fanmiaothu/ 新浪微博]
 
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B.Eng @ [http://english.bupt.edu.cn/ Beijing University of Posts and Telecommunications] [北京邮电大学 软件学院 软件工程专业 工学学士学位] —— 导师:[http://baike.baidu.com/view/9021485.htm 吴国仕]、李晶;
 
 
Ph.D. in C.S. @ [http://www.tsinghua.edu.cn/publish/newthuen/index.html Tsinghua University] [清华大学 计算机科学与技术系 计算机科学与技术专业 工学博士学位] —— 导师:[http://cslt.riit.tsinghua.edu.cn/~fzheng/  郑方]、[http://cslt.riit.tsinghua.edu.cn/~qzhou/chs/index.htm 周强];
 
 
Visiting Scholar @ [https://www.nyu.edu/ New York University] [国家留学基金委 公派联合培养博士 美国纽约大学计算机系] —— 导师:[http://cs.nyu.edu/grishman/ Ralph Grishman];
 
 
Postdoctoral Scholar @ [http://research.baidu.com/ Baidu Research] & [http://www.tsinghua.edu.cn/publish/newthuen/index.html Tsinghua University] [百度-清华大学联合培养博士后  清华大学软件学院 信息系统工程专业] —— 联合导师:[http://ir.baidu.com/phoenix.zhtml?c=188488&p=irol-govBio&ID=256144 王海峰 (百度)]、[http://www.thss.tsinghua.edu.cn/publish/soft/3641/2010/20101214090035662150715/20101214090035662150715_.html 王建民 (清华大学)];
 
 
 
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[https://scholar.google.com/citations?user=aPlHReAAAAAJ&hl=en Google Scholar(谷歌学术档案)]
 
 
[http://dblp.uni-trier.de/pers/hd/f/Fan:Miao DBLP(DBLP论文索引)]
 
 
[http://www.kaggle.com/michaelfan Kaggle Profile(Kaggle竞赛成绩)]
 
 
 
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[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/a/a9/B.ENG_Dissertation_-Miao_Fan-.pdf Best B.Eng Dissertation @ Beijing University of Posts and Telecommunications (北京邮电大学本科优秀毕业设计:基于百科知识的中文自动问题生成技术的研究与系统实现)]
 
 
[https://onedrive.live.com/redir?resid=76645C25A8914A0B!8071&authkey=!AIYUeWmYlXPFWSU&ithint=file%2cpptx Ph.D. Research Proposal(清华大学博士开题报告:基于低维表示的大规模实体关系挖掘技术研究)]
 
 
[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/0/09/%E8%8C%83%E6%B7%BC-%E5%8D%9A%E5%A3%AB%E5%AD%A6%E4%BD%8D%E8%AE%BA%E6%96%87%E7%94%B5%E5%AD%90%E7%89%88.pdf Best Ph.D. Thesis Nomination @ Tsinghua University (清华大学计算机系优秀博士毕业生;清华大学校级优秀博士论文提名:基于表示学习的知识挖掘研究)] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/8/89/%E8%8C%83%E6%B7%BC-%E5%8D%9A%E5%A3%AB%E7%AD%94%E8%BE%A9-%E6%9C%80%E7%BB%88%E7%89%88.pdf Slides of thesis defense (答辩PPT)] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/f/f2/MF_PhD_thesis_references.pdf References(已发表的学术论文集)]
 
 
[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/5/59/Special_talks_NYU--M.F.-.pdf Slides of NYU Special Talks(美国纽约大学授课讲义:Statistical NLP: A Machine Learning Perspective)]
 
 
 
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[https://union-click.jd.com/jdc?d=lKjrlR&come=appmessage 范淼、李超;《Python机器学习及实践:从零开始通往Kaggle竞赛之路》; 清华大学出版社 (Tsinghua University Press)] [http://www.tup.tsinghua.edu.cn/upload/books/yz/069392-01.pdf 书籍样章] [https://union-click.jd.com/jdc?d=lKjrlR&come=appmessage 京东购书] [http://pan.baidu.com/s/1bGp15G 源代码 (Source Codes)] [https://git.coding.net/fanmiao_thu/Python_ML_and_Kaggle.git Github] [勘误列表]
 
 
[范淼;《PySpark 2.0 分布式机器学习与大数据分析》 ;清华大学出版社 (Tsinghua University Press) 计划出版] [https://www.youtube.com/playlist?list=PL-x35fyliRwhDv3g1dae8v2F6-_bzBfGK YouTube视频] [源代码(Source Codes)]
 
 
[范淼;《Python深度学习实践:探秘谷歌TensorFlow》] [https://www.tensorflow.org/ Google TensorFlow] [https://arxiv.org/pdf/1610.01178v1.pdf A Tour of TensorFlow] [https://www.udacity.com/course/deep-learning--ud730 谷歌官方视频教程] [https://www.youtube.com/playlist?list=PLXO45tsB95cKI5AIlf5TxxFPzb-0zeVZ8 周莫烦简易视频教程]
 
 
[范淼;《Python推荐系统实战》(Recommender System in Practice with Python Programming)] [https://arxiv.org/pdf/1606.07792v1.pdf Wide & Deep Learning for Recommender Systems]
 
 
 
 
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[http://www.deeplearningbook.org/contents/acknowledgements.html Deep Learning(校对图书)] [http://www.deeplearningbook.org 公开下载网址] [https://github.com/exacity/deeplearningbook-chinese/releases/download/v0.5-beta/dlbook_cn_v0.5-beta.pdf 中文版] [http://deeplearning.stanford.edu/wiki/index.php/UFLDL_Tutorial Tutorial(教程)]
 
 
[https://www.cs.toronto.edu/~hinton/absps/NatureDeepReview.pdf Yann LeCun, Yoshua Bengio & Geoffrey Hinton; Nature: Review of Deep Learning] 
 
 
[http://www.cs.cmu.edu/~tom/pubs/Science-ML-2015.pdf M.I.Jordan & T.M.Mitchell; Science: Machine learning Trends, perspectives, and prospects ]
 
 
[http://cs229.stanford.edu/materials.html  Machine Learning (Stanford University)] [https://www.youtube.com/playlist?list=PLC5F94EBABE15D569 YouTube(视频)] [http://open.163.com/special/opencourse/machinelearning.html 网易公开课视频]
 
 
[http://mmds.org/ Mining of Massive Datasets] [https://www.youtube.com/channel/UC_Oao2FYkLAUlUVkBfze4jg Youtube(视频)]
 
 
[http://spark.apache.org/docs/latest/api/python/index.html  PySpark 2.x] [https://www.youtube.com/playlist?list=PL-x35fyliRwhDv3g1dae8v2F6-_bzBfGK YouTube视频] [https://www.gitbook.com/book/jaceklaskowski/mastering-apache-spark/details 参考文档]
 
 
[http://incompleteideas.net/sutton/book/bookdraft2017nov5.pdf Reinforcement Learning: An Introduction (MIT Press)]
 
 
[https://www.cs.cornell.edu/jeh/book2016June9.pdf Foundations of Data Science]
 
 
[https://courses.csail.mit.edu/6.042/spring17/mcs.pdf Mathematics for Computer Science]
 
 
[http://www.mlyearning.org/ Machine Learning Yearning]
 
 
[http://www.wildml.com/ WildML]
 
 
[https://morvanzhou.github.io/tutorials/ Morvan莫烦机器学习视频]
 
 
 
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Pre-mentors/advisers:  [http://cs.nyu.edu/grishman/ Ralph Grishman] [http://stat.rutgers.edu/home/pingli/doc/PingLiCV.pdf Ping Li] [https://scholar.google.com.hk/citations?user=jgy4jCAAAAAJ&hl=zh-CN Haifeng Wang] [http://www.thss.tsinghua.edu.cn/publish/soft/3641/2010/20101214090035662150715/20101214090035662150715_.html Jianmin Wang] [http://baike.baidu.com/view/9021485.htm Guoshi Wu] [http://cslt.riit.tsinghua.edu.cn/~fzheng/ Thomas Fang Zheng] [http://cslt.riit.tsinghua.edu.cn/~qzhou/chs/index.htm Qiang Zhou]
 
 
Outstanding Friends: [http://dblp.uni-trier.de/pers/hd/g/Gan:Chuang Chuang Gan] [https://sites.google.com/site/wenbinghuangshomepage/ Wenbing Huang] [http://www.ruiyan.me/ Rui Yan] [http://yindawei.com Dawei Yin] [http://ir.hit.edu.cn/~zhaosq/ Shiqi Zhao] [https://www.microsoft.com/en-us/research/people/jiazhan/ Jianwen Zhang]
 

2022年1月20日 (四) 07:12的最后版本

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