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| | =参考文献= | | =参考文献= |
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| − | ===基础===
| + | [[大数据智能-参考文献]] |
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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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| − | # Bjarne Stroustrup, The C++ programming language. Pearson Education, 2013.
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| − | # Weiss, Mark Allen, Data structures and algorithm analysis in Java, Addison-Wesley Longman Publishing Co., Inc., 1998.
| + | |
| − | # David Flanagan, JavaScript: The definitive guide: Activate your web pages. " O'Reilly Media, Inc.", 2011.
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| − | # Miguel Grinberg, Flask Web Development: Developing Web Applications with Python. O'Reilly Media, Inc., 2014.
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| − | ===深度学习===
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| − | # Yoshua Bengio, Ian Goodfellow, Aaron Courville, Deep Learning, MIT Press, 2016. [http://www.deeplearningbook.org/ DeepLearningBook]
| + | |
| − | # Google brain team, TensorFlow: Large-scale machine learning on heterogeneous systems, whitepaper, 2015.
| + | |
| − | # Vijay Agneeswaran, Real-Time Applications with Storm, Spark, and More Hadoop Alternatives, 2014.
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| − | ===计算机围棋===
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| − | # Mastering the game of Go with deep neural networks and tree search, nature 2015.
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| − | # Better Computer Go Player with Neural Network and Long-term Prediction, ICLR 2016.
| + | |
| − | # Pachi: State of the art open source Go program, Advances in computer games, Springer Berlin Heidelberg, 2011.
| + | |
| − | # Training Deep Convolutional Neural Networks to Play Go, JMLR 2015.
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以完成一种以大数据为基础的智能系统的原型开发为目标，在实践中运用大数据智能理论与技术。团队成员学习大数据系统与机器智能的理论知识和专业技能，完成项目团队结构设计和原型开发的实践环节，全面提高学生的技术实践能力。
