“大数据智能-参考文献”版本间的差异

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=== 基础 ===
 
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==== 编程语言 ====
 
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# Google C++ Style [https://google.github.io/styleguide/cppguide.html Google C++ Style]
 
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# PEP 8 - Style Guide for Python Code [https://www.python.org/dev/peps/pep-0008/ PEP_8]
 
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# David Flanagan, JavaScript: The definitive guide: Activate your web pages. " O'Reilly Media, Inc.", 2011.
 
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# Weiss, Mark Allen, Data structures and algorithm analysis in Java, Addison-Wesley Longman Publishing Co., Inc., 1998.
 
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# Bjarne Stroustrup, The C++ programming language. Pearson Education, 2013.
 
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==== 计算机应用基础 ====
 
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# John L. Hennessy, and David A. Patterson. Computer architecture: a quantitative approach. Elsevier, 2011.
 
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# Neil Matthew, and Richard Stones. Beginning linux programming. John Wiley & Sons, 2011.
 
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# Miguel Grinberg, Flask Web Development: Developing Web Applications with Python. O'Reilly Media, Inc., 2014.
 
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=== 数据管理 ===
 
=== 数据管理 ===
  

2017年6月6日 (二) 02:56的版本

数据管理

  1. Leskovec, Jure, Anand Rajaraman, and Jeffrey David Ullman. Mining of massive datasets. Cambridge University Press, 2014. MMDS_book
  2. Vijay Agneeswaran, Real-Time Applications with Storm, Spark, and More Hadoop Alternatives, 2014.

大数据智能

  1. 刘知远，崔安欣等，大数据智能：互联网时代的机器学习和自然语言处理技术. 电子工业出版社，2016年。

深度学习

  1. Yoshua Bengio, Ian Goodfellow, Aaron Courville, Deep Learning, MIT Press, 2016. DeepLearningBook
  2. Google brain team, TensorFlow: Large-scale machine learning on heterogeneous systems, whitepaper, 2015.

计算机围棋

  1. Mastering the game of Go with deep neural networks and tree search, nature 2015.
  2. Better Computer Go Player with Neural Network and Long-term Prediction, ICLR 2016.
  3. Pachi: State of the art open source Go program, Advances in computer games, Springer Berlin Heidelberg, 2011.
  4. Training Deep Convolutional Neural Networks to Play Go, JMLR 2015.
取自“http://wiki.icenter.tsinghua.edu.cn/icenterwiki/index.php?title=大数据智能-参考文献&oldid=43501”