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README.md

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-# Machine-Learning-Book #
+# Machine-Learning-Book #
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+​	该仓库主要存储本人所阅读机器学习相关pdf书籍及其个人笔记笔记，其主要目的是提供一个在任何地点任何时候阅读的书籍都是最新的(版本控制系统)，使其类似于kindle的功能(笔记)。(本人经常阅读pdf书籍，在原始pdf书籍上做笔记，但有的的时候所阅读的pdf的笔记--不同的电脑上，不是最新的而困扰)。。。。。。。。。。。。。。ps\:经本人测试，github的版本控制系统能够对pdf的笔记作出相关的版本控制
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+## book ##
+
+**Algorithms**. 0th Edition. Jeff Erickson.2018
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+**Natural Language Processing**. 0th Edition. Jacob Eisenstein. 2018
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+**Statistical Thinking for the 21st Century**. Draft. Russell A. Poldrack.12.2018
+
+**数字经济下的算法力量-阿里算法年度精选集**. 阿里巴巴集团,2018
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+**强化学习在阿里的技术演进与业务创新**. 阿里巴巴集团,2018
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+**Speech and Language Processing**. 3th Edition draft.Daniel Jurafsky,James H. Martin. 2017
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+**A course in machine learning**. Hal Daumé III. 2017
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+**Bayesian Reasoning and Machine Learning**. Edition draft. David Barber.2017
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+**Artificial inteligence**. 2017
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+**TensorFlow Machine Learning Cookbook**. 2017
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+**深度学习**. 2017
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+**阿里技术-年度精选-上**. 阿里巴巴集团,2017
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+**阿里技术-年度精选-下**. 阿里巴巴集团,2017
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+**Deep Learning**. Ian Goodfellow ,Yoshua Bengio , Aaron Courville. MIT,2016
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+**Reinforcement Learning An Introduction**. 2th Edition draft. Richard S. Sutton and Andrew G. Barto. 2016
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+**Think Data Structures Algorithms and Information Retrieval in Java**. 1th Edition. Allen B. Downey. Green Tea Press,2016
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+**神经⽹络与深度学习**. Xiaohu Zhu,Freeman Zhang. 2016
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+**Python网络数据采集**. 陶俊杰,陈小莉. 人民邮电出版社出版,2016
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+**深入理解Spark核心思想与源码分析**. 耿嘉安. 机械工业出版社,2015
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+**Think Stats Exploratory Data Analysis in Python**. Allen B. Downey. Green Tea Press,2014
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+**模式识别与机器学习**. 马春鹏. 2014
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+**Building Machine Learning Systems with Python**. Willi Richert,Luis Pedro Coelho.2013 [相关资源](https://github.com/YSZYCF/Machine-Learning-Book-Resource/tree/master/Building%20Machine%20Learning%20Systems%20with%20Python)
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+**Python For Data Analysis**. Julie Steele and Meghan Blanchette. Oreilly,2013 [中文版资源](https://github.com/YSZYCF/Machine_Learning_Book_Pirated/blob/master/%E5%88%A9%E7%94%A8Python%E8%BF%9B%E8%A1%8C%E6%95%B0%E6%8D%AE%E5%88%86%E6%9E%90--%E4%B8%AD%E6%96%87%E7%89%88.pdf)
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+
+**数据可视化实战-使用D3设计交互式图表**. 李松峰.人民邮电出版社,2013
+**Machine Learning A Probabilistic Perspective**. Kevin P. Murphy. MIT,2012
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+**Ensemble Methods Foundations and Algorithms**. Zhi-Hua Zhou. CRC press,2012
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+**Boosting Foundations and Algorithms**. Robert E. Schapire,Yoav Freund. MIT,2012
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+**Planning with Markov Decision Processes An AI Perspective**. Mausam and Andrey Kolobov. 2012
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+**Machine Learning The Art and Science of Algorithms that Make Sense of Data**. Peter Flach.Cambridge,2012 [ppt资源](https://github.com/YSZYCF/Machine-Learning-Book-Resource/tree/master/Machine%20Learning%20The%20Art%20and%20Science%20of%20Algorithms%20that%20Make%20Sense%20of%20Data)
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+**Machine Learning for Hackers**. Drew Conway and John Myles White. oreilly,2012
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+**统计学习方法**. 李航. 清华大学出版社,2012
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+**推荐系统实践**. 项亮. 人民邮电出版社,2012
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+**大数据互联网大规模数据挖掘与分布式处理**. 王斌. 人民邮电出版社,2012
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+**Think Stats Probability and Statistics for Programmers**. 1th Edition. Allen B. Downey. Green Tea Press,2011
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+**Data Mining-Practical Machine Learning Tools and Techniques**. 3th Edition. Ian H. Witten,Eibe Frank,Mark A. Hall.Elsevier,2011
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+**Adaptive Representations for Reinforcement Learning**. Shimon Whiteson. 2010
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+**Introduction to Machine Learning**. 2th Edition. Ethem Alpaydın. MIT,2010
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+**Reinforcement learning and dynamic programming using function approximators**. Lucian Bus¸oniu, Robert Babuˇska, Bart De Schutter, and Damien Ernst. 2009
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+**The Elements of Statistical Learning Data Mining, Inference, and Prediction**. 2th Edition. Springer, 2008
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+**Neural Networks and Learning Machines**. 3th Edition. Simon Haykin.2008 [中文资源](https://github.com/YSZYCF/Machine-Learning-Book-Resource/tree/master/Neural%20networks%20and%20learning%20machines)
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+**Stanford University-cs229-lecture-note**. Andrew Ng. 2008
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+**Introduction to Machine Learning**. Amnon Shashua. 2008
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+**Reinforcement Learning**. Cornelius Weber, Mark Elshaw and Norbert Michael Mayer. 2008
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+**Programming Collective Intelligence**. Toby Segaran. oreilly,2007
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+**Pattern Recognition and Machine Learning**. Christopher M. Bishop.Springer.2006
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+**Gaussian Processes for Machine Learning**. Carl Edward Rasmussen and Christopher K. I. Williams. MIT,2006
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+**Information Theory, Inference, and Learning Algorithms**. David J.C. MacKay. Cambridge University Press,2005
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+**Machine Learning Neural and Statistical Classification**. D. Michie, D.J. Spiegelhalter, C.C. Taylor. 1994
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+**Pattern Classification**. 2th Edition. Richard O.Duda,Peter E.Hart,David G.Stork [中文资源](https://github.com/YSZYCF/Machine_Learning_Book_Pirated/blob/master/%E6%A8%A1%E5%BC%8F%E5%88%86%E7%B1%BB-%E7%AC%AC%E4%BA%8C%E7%89%88.pdf)
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+**All of Statistics A Concise Course in Statistical Inference**. Larry Wasserman. Springer
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+**机器学习-Mitchell-中文-清晰版**
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+**机器学习实战_中文版**  [相关资源](https://github.com/YSZYCF/Machine-Learning-Book-Resource/tree/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%AE%9E%E6%88%98)
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+**数据挖掘**
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+**TensorFlow 官方文档中文版 - v1.2**
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+## ps ##
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+* 统计学习方法 该书不可编辑,望君贡献
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+## Todo ##
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+* 重构书籍结构
+* Reinforcement Learning 该书的某些页面需要重新裁剪
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