Machine-Learning-Book

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

book

Algorithms. 0th Edition. Jeff Erickson.2018

Natural Language Processing. 0th Edition. Jacob Eisenstein. 2018

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

强化学习在阿里的技术演进与业务创新. 阿里巴巴集团,2018

Speech and Language Processing. 3th Edition draft.Daniel Jurafsky,James H. Martin. 2017

A course in machine learning. Hal Daumé III. 2017

Bayesian Reasoning and Machine Learning. Edition draft. David Barber.2017

Artificial inteligence. 2017

TensorFlow Machine Learning Cookbook. 2017

深度学习. 2017

阿里技术-年度精选-上. 阿里巴巴集团,2017

阿里技术-年度精选-下. 阿里巴巴集团,2017

Deep Learning. Ian Goodfellow ,Yoshua Bengio , Aaron Courville. MIT,2016

Reinforcement Learning An Introduction. 2th Edition draft. Richard S. Sutton and Andrew G. Barto. 2016

Think Data Structures Algorithms and Information Retrieval in Java. 1th Edition. Allen B. Downey. Green Tea Press,2016

神经⽹络与深度学习. Xiaohu Zhu,Freeman Zhang. 2016

Python网络数据采集. 陶俊杰,陈小莉. 人民邮电出版社出版,2016

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

Think Stats Exploratory Data Analysis in Python. Allen B. Downey. Green Tea Press,2014

模式识别与机器学习. 马春鹏. 2014

Building Machine Learning Systems with Python. Willi Richert,Luis Pedro Coelho.2013 相关资源

Python For Data Analysis. Julie Steele and Meghan Blanchette. Oreilly,2013 中文版资源

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

Ensemble Methods Foundations and Algorithms. Zhi-Hua Zhou. CRC press,2012

Boosting Foundations and Algorithms. Robert E. Schapire,Yoav Freund. MIT,2012

Planning with Markov Decision Processes An AI Perspective. Mausam and Andrey Kolobov. 2012

Machine Learning The Art and Science of Algorithms that Make Sense of Data. Peter Flach.Cambridge,2012 ppt资源

Machine Learning for Hackers. Drew Conway and John Myles White. oreilly,2012

Foundations of Machine Learning. Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar.MIT,2012

统计学习方法. 李航. 清华大学出版社,2012

推荐系统实践. 项亮. 人民邮电出版社,2012

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

Think Stats Probability and Statistics for Programmers. 1th Edition. Allen B. Downey. Green Tea Press,2011

Data Mining-Practical Machine Learning Tools and Techniques. 3th Edition. Ian H. Witten,Eibe Frank,Mark A. Hall.Elsevier,2011

Adaptive Representations for Reinforcement Learning. Shimon Whiteson. 2010

Introduction to Machine Learning. 2th Edition. Ethem Alpaydın. MIT,2010

Reinforcement learning and dynamic programming using function approximators. Lucian Bus¸oniu, Robert Babuˇska, Bart De Schutter, and Damien Ernst. 2009

The Elements of Statistical Learning Data Mining, Inference, and Prediction. 2th Edition. Springer, 2008

Neural Networks and Learning Machines. 3th Edition. Simon Haykin.2008 中文资源

Stanford University-cs229-lecture-note. Andrew Ng. 2008

Introduction to Machine Learning. Amnon Shashua. 2008

Reinforcement Learning. Cornelius Weber, Mark Elshaw and Norbert Michael Mayer. 2008

Programming Collective Intelligence. Toby Segaran. oreilly,2007

Pattern Recognition and Machine Learning. Christopher M. Bishop.Springer.2006

Gaussian Processes for Machine Learning. Carl Edward Rasmussen and Christopher K. I. Williams. MIT,2006

Information Theory, Inference, and Learning Algorithms. David J.C. MacKay. Cambridge University Press,2005

Machine Learning Neural and Statistical Classification. D. Michie, D.J. Spiegelhalter, C.C. Taylor. 1994

Pattern Classification. 2th Edition. Richard O.Duda,Peter E.Hart,David G.Stork 中文资源

All of Statistics A Concise Course in Statistical Inference. Larry Wasserman. Springer

The Top Ten Algorithms in Data Mining

机器学习-Mitchell-中文-清晰版

机器学习实战_中文版 相关资源

数据挖掘

TensorFlow 官方文档中文版 - v1.2

ps

统计学习方法该书不可编辑,望君贡献

Todo

重构书籍结构
Reinforcement Learning 该书的某些页面需要重新裁剪
推荐系统实践. 项亮. 人民邮电出版社,2012
Stanford University-cs229-lecture-note. Andrew Ng. 2008
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
模式识别与机器学习. 马春鹏. 2014
深度学习. 2017

深度学习

序列建模

10.3 -- 10.11 已读
联合概率分布和条件概率分母架构的设计(框图)?
序列到向量、向量到序列、固定序列到固定序列、序列到变长序列的设计及其相关细节?(框图)
跳跃连接和删除连接的具体图例以及两者的区别?
递归神经网络的具体细节以及如何实现?
长期依赖的解决方案?
回声状态网络?
渗漏单元、线性自连接单元、时间尺度是什么以及图例?
为什么会产生LSTM、LSTM的灵感、LSTM的设计思想?
10.11 需要重读

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
A course in machine learning.pdf		A course in machine learning.pdf
Adaptive Representations for Reinforcement Learning.pdf		Adaptive Representations for Reinforcement Learning.pdf
Algorithms-0th Edition.pdf		Algorithms-0th Edition.pdf
All of Statistics A Concise Course in Statistical Inference.pdf		All of Statistics A Concise Course in Statistical Inference.pdf
Artificial inteligence.pdf		Artificial inteligence.pdf
Bayesian Reasoning and Machine Learning-Edition draft.pdf		Bayesian Reasoning and Machine Learning-Edition draft.pdf
Boosting Foundations and Algorithms.pdf		Boosting Foundations and Algorithms.pdf
Building Machine Learning Systems with Python - Richert, Coelho.pdf		Building Machine Learning Systems with Python - Richert, Coelho.pdf
Data Mining-Practical Machine Learning Tools and Techniques.pdf		Data Mining-Practical Machine Learning Tools and Techniques.pdf
Deep Learning.pdf		Deep Learning.pdf
Ensemble methods Foundations and Algorithms.pdf		Ensemble methods Foundations and Algorithms.pdf
Foundations of Machine Learning.pdf		Foundations of Machine Learning.pdf
Gaussian Processes for Machine Learning.pdf		Gaussian Processes for Machine Learning.pdf
Information Theory, Inference, and Learning Algorithms.pdf		Information Theory, Inference, and Learning Algorithms.pdf
Introduction to Machine Learning-2th Edition-Ethem Alpaydın.pdf		Introduction to Machine Learning-2th Edition-Ethem Alpaydın.pdf
Introduction to Machine Learning.pdf		Introduction to Machine Learning.pdf
Machine Learning A Probabilistic Perspective.pdf		Machine Learning A Probabilistic Perspective.pdf
Machine Learning Neural and Statistical Classification.pdf		Machine Learning Neural and Statistical Classification.pdf
Machine Learning The Art and Science of Algorithms that Make Sense of Data.pdf		Machine Learning The Art and Science of Algorithms that Make Sense of Data.pdf
Machine Learning for Hackers.pdf		Machine Learning for Hackers.pdf
Natural Language Processing .pdf		Natural Language Processing .pdf
Pattern Classification-2th Edition.pdf		Pattern Classification-2th Edition.pdf
Pattern Recognition and Machine Learning.pdf		Pattern Recognition and Machine Learning.pdf
Planning with Markov Decision Processes An AI Perspective.pdf		Planning with Markov Decision Processes An AI Perspective.pdf
Programming Collective Intelligence.pdf		Programming Collective Intelligence.pdf
Python For Data Analysis.pdf		Python For Data Analysis.pdf
Python网络数据采集.pdf		Python网络数据采集.pdf
README.md		README.md
Reinforcement Learning An Introduction-2th Edition draft.pdf		Reinforcement Learning An Introduction-2th Edition draft.pdf
Reinforcement Learning.pdf		Reinforcement Learning.pdf
Reinforcement learning and dynamic programming using function approximators.pdf		Reinforcement learning and dynamic programming using function approximators.pdf
Speech and Language Processing-3th Edition draft.pdf		Speech and Language Processing-3th Edition draft.pdf
Stanford University-cs229-lecture-note.pdf		Stanford University-cs229-lecture-note.pdf
Statistical Thinking for the 21st Century-Draft-2018.pdf		Statistical Thinking for the 21st Century-Draft-2018.pdf
TensorFlow Machine Learning Cookbook.pdf		TensorFlow Machine Learning Cookbook.pdf
TensorFlow 官方文档中文版 - v1.2.pdf		TensorFlow 官方文档中文版 - v1.2.pdf
The Elements of Statistical Learning Data Mining, Inference, and Prediction_第三版.pdf		The Elements of Statistical Learning Data Mining, Inference, and Prediction_第三版.pdf
The Top Ten Algorithms in Data Mining.pdf		The Top Ten Algorithms in Data Mining.pdf
Think Data Structures Algorithms and Information Retrieval in Java.pdf		Think Data Structures Algorithms and Information Retrieval in Java.pdf
Think Stats Exploratory Data Analysis in Python.pdf		Think Stats Exploratory Data Analysis in Python.pdf
Think Stats Probability and Statistics for Programmers.pdf		Think Stats Probability and Statistics for Programmers.pdf
neural networks and Learning Machines.3ed.2009.pdf		neural networks and Learning Machines.3ed.2009.pdf
大数据互联网大规模数据挖掘与分布式处理.pdf		大数据互联网大规模数据挖掘与分布式处理.pdf
强化学习在阿里的技术演进与业务创新.pdf		强化学习在阿里的技术演进与业务创新.pdf
推荐系统实践.pdf		推荐系统实践.pdf
数字经济下的算法力量-阿里算法年度精选集.pdf		数字经济下的算法力量-阿里算法年度精选集.pdf
数据可视化实战-使用D3设计交互式图表.pdf		数据可视化实战-使用D3设计交互式图表.pdf
数据挖掘.pdf		数据挖掘.pdf
机器学习-Mitchell-中文-清晰版.pdf		机器学习-Mitchell-中文-清晰版.pdf
机器学习实战_中文版.pdf		机器学习实战_中文版.pdf
模式识别与机器学习.pdf		模式识别与机器学习.pdf
深入理解Spark 核心思想与源码分析.pdf		深入理解Spark 核心思想与源码分析.pdf
深度学习.pdf		深度学习.pdf
神经网络与深度学习.pdf		神经网络与深度学习.pdf
统计学习方法.李航.pdf		统计学习方法.李航.pdf
阿里技术-年度精选-上.pdf		阿里技术-年度精选-上.pdf
阿里技术-年度精选-下.pdf		阿里技术-年度精选-下.pdf

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Machine-Learning-Book

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