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资源 | 任何阶段的学习者都适用的参考:机器学习领域书目全集

选自Machine Learning Mastery

机器之心编译

参与:李泽南、朱思颖


来自 Swinburne 科技大学的 Jason Brownlee 博士为我们带来了最新一期的机器学习书目,内容覆盖科普、各级教材以及不同编程语言的机器学习应用。


学习是一种理性的投资,每当花费十几个小时读完一本书,你就能领略到前人数年积累的经验。


在阅读了市面上大多数机器学习书籍后,作者列出了最新机器学习领域推荐图书,并使用了使用不同分类方式进行了整理:


按类型:教科书,热门学科等;

按主题:Python,深度学习等;

按出版商:Packt,O'Reilly 等;

……


如何使用


1. 找到你最感兴趣的分类方式,找到需要的主题;

2. 在你选择的主题中挑选;

3. 购买图书;

4. 从头到尾阅读;

5. 继续找下一本。


拥有一本书和了解它的内容是完全不同的两种概念——你必须真正阅读它们。

请先问问自己:你有没有读完过一本机器学习的书?


机器学习图书——按类型分


最流行机器学习科普图书


以下图书适用于大多数读者。它们点到了机器学习和数据科学的精华之处,却没有使用枯燥的理论或应用细节。这份书单也包括了一些流行的「统计思想」科普书籍。


The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World 

地址:http://www.amazon.com/dp/0465065708?tag=inspiredalgor-20


Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die 

地址:http://www.amazon.com/dp/1119145678?tag=inspiredalgor-20


The Signal and the Noise: Why So Many Predictions Fail–but Some Don't 

地址:http://www.amazon.com/dp/0143125087?tag=inspiredalgor-20


Naked Statistics: Stripping the Dread from the Data 

地址:http://www.amazon.com/dp/039334777X?tag=inspiredalgor-20


The Drunkard's Walk: How Randomness Rules Our Lives 

地址:http://www.amazon.com/dp/0307275175?tag=inspiredalgor-20



其中最值得推荐的一本是:《The Signal and the Noise》。


适用于机器学习初学者的书籍


以下列出最适用于初学者的书籍。希望入门的读者同时也需要参考科普图书(上一条)以及行业应用图书(下一条)。


Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

地址:http://www.amazon.com/dp/1449361323?tag=inspiredalgor-20


Data Smart: Using Data Science to Transform Information into Insight 

地址:http://www.amazon.com/dp/111866146X?tag=inspiredalgor-20


Data Mining: Practical Machine Learning Tools and Techniques 

地址:http://www.amazon.com/dp/0128042915?tag=inspiredalgor-20


Doing Data Science: Straight Talk from the Frontline 

地址:http://www.amazon.com/dp/1449358659?tag=inspiredalgor-20



在这其中最重要的一本是:《Data Mining: Practical Machine Learning Tools and Techniques》。


机器学习入门书籍——高级


以下是适用于希望入门机器学习的本科学生和开发者的书籍,内容包含了机器学习的很多话题,注重如何解决问题,而不是介绍理论。


Machine Learning for Hackers: Case Studies and Algorithms to Get You Started 

地址:http://www.amazon.com/dp/B007A0BNP4?tag=inspiredalgor-20


Machine Learning in Action

地址:http://www.amazon.com/dp/1617290181?tag=inspiredalgor-20

Programming Collective Intelligence: Building Smart Web 2.0 Applications 

地址:http://www.amazon.com/dp/0596529325?tag=inspiredalgor-20


An Introduction to Statistical Learning: with Applications in R 

地址:http://www.amazon.com/dp/1461471370?tag=inspiredalgor-20


Applied Predictive Modeling 

地址:http://www.amazon.com/dp/1461468485?tag=inspiredalgor-20



其中最值得推荐的一本是:《An Introduction to Statistical Learning: with Applications in R》


机器学习教材


以下列出了机器学习领域目前最流行的教科书。它们会在研究生课程中出现,包含方法与理论的解读。


The Elements of Statistical Learning: Data Mining, Inference, and Prediction 

地址:http://www.amazon.com/dp/0387848576?tag=inspiredalgor-20


Pattern Recognition and Machine Learning 

地址:http://www.amazon.com/dp/0387310738?tag=inspiredalgor-20


Machine Learning: A Probabilistic Perspective 

地址:http://www.amazon.com/dp/0262018020?tag=inspiredalgor-20


Learning From Data 

地址:http://www.amazon.com/dp/B00YDJC98K?tag=inspiredalgor-20


Machine Learning 

地址:http://www.amazon.com/dp/0070428077?tag=inspiredalgor-20


Machine Learning: The Art and Science of Algorithms that Make Sense of Data 

地址:http://www.amazon.com/dp/1107422221?tag=inspiredalgor-20


Foundations of Machine Learning 

地址:http://www.amazon.com/dp/026201825X?tag=inspiredalgor-20



其中的重点是:《The Elements of Statistical Learning: Data Mining, Inference, and Prediction》


机器学习图书——按主题分


有关 R 语言在机器学习中如何应用的图书。


The Elements of Statistical Learning: Data Mining, Inference, and Prediction 

地址:http://www.amazon.com/dp/0387848576?tag=inspiredalgor-20


Pattern Recognition and Machine Learning

地址:http://www.amazon.com/dp/0387310738?tag=inspiredalgor-20


Machine Learning: A Probabilistic Perspective 

地址:http://www.amazon.com/dp/0262018020?tag=inspiredalgor-20


Learning From Data 

地址:http://www.amazon.com/dp/B00YDJC98K?tag=inspiredalgor-20


Machine Learning 

地址:http://www.amazon.com/dp/0070428077?tag=inspiredalgor-20


Machine Learning: The Art and Science of Algorithms that Make Sense of Data 

地址:http://www.amazon.com/dp/1107422221?tag=inspiredalgor-20


Foundations of Machine Learning 

地址:http://www.amazon.com/dp/026201825X?tag=inspiredalgor-20


这方面的首选图书是:《The Elements of Statistical Learning: Data Mining, Inference, and Prediction》。


Python 机器学习


以下列出 Python 机器学习热门书籍


Python Machine Learning 

地址:http://www.amazon.com/dp/1783555130?tag=inspiredalgor-20


Data Science from Scratch: First Principles with Python 

地址:http://www.amazon.com/dp/149190142X?tag=inspiredalgor-20


Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques for Building Intelligent Systems 

地址:http://www.amazon.com/dp/1491962291?tag=inspiredalgor-20


Introduction to Machine Learning with Python: A Guide for Data Scientists 

地址:http://www.amazon.com/dp/1449369413?tag=inspiredalgor-20


Vital Introduction to Machine Learning with Python: Best Practices to Improve and Optimize Machine Learning Systems and Algorithms 

地址:http://www.amazon.com/dp/B01N4FUDSE?tag=inspiredalgor-20


Machine Learning in Python: Essential Techniques for Predictive Analysis 

地址:http://www.amazon.com/dp/1118961749?tag=inspiredalgor-20


Python Data Science Handbook: Essential Tools for Working with Data 

地址:http://www.amazon.com/dp/1491912057?tag=inspiredalgor-20


Introducing Data Science: Big Data, Machine Learning, and more, using Python tools 地址:http://www.amazon.com/dp/1633430030?tag=inspiredalgor-20


Real-World Machine Learning 

地址:http://www.amazon.com/dp/1617291927?tag=inspiredalgor-20



最值得注意的当然是《Python 机器学习》了。


深度学习


注意:深度学习的图书目前还比较稀缺,以下这份列表只能保证数量,而不是质量。


Deep Learning 

地址:http://www.amazon.com/dp/0262035618?tag=inspiredalgor-20


Deep Learning: A Practitioner's Approach 

地址:http://www.amazon.com/dp/1491914254?tag=inspiredalgor-20


Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms 

地址:http://www.amazon.com/dp/1491925612?tag=inspiredalgor-20


Learning TensorFlow: A guide to building deep learning systems 

地址:http://www.amazon.com/dp/1491978511?tag=inspiredalgor-20


Machine Learning with TensorFlow 

地址:http://www.amazon.com/dp/1617293873?tag=inspiredalgor-20


TensorFlow Machine Learning Cookbook

地址:http://www.amazon.com/dp/1786462168?tag=inspiredalgor-20


Getting Started with TensorFlow 

地址:http://www.amazon.com/dp/1786468573?tag=inspiredalgor-20


TensorFlow for Machine Intelligence: A Hands-On Introduction to Learning Algorithms 

地址:http://www.amazon.com/dp/1939902452?tag=inspiredalgor-20



其中最重要的一本书当然是:Yoshua Bengio 和 Ian Goodfellow 所著的《Deep Learning》。


时序序列预测


目前时序序列预测在实际应用中主要是由 R 语言的平台所主导。


Time Series Analysis: Forecasting and Control

地址:http://www.amazon.com/dp/1118675029?tag=inspiredalgor-20


Practical Time Series Forecasting with R: A Hands-On Guide

地址:http://www.amazon.com/dp/0997847913?tag=inspiredalgor-20


Introduction to Time Series and Forecasting

地址:http://www.amazon.com/dp/3319298526?tag=inspiredalgor-20


Forecasting:principles and practice

地址:http://www.amazon.com/dp/0987507109?tag=inspiredalgor-20





  • 最优质的入门介绍书籍是 Forecasting:principles and practice。

  • 时序序列最优质的教科书是 Time Series Analysis: Forecasting and Control。


机器学习图书——按照出版商分类


目前活跃在机器学习领域的出版商主要有: O'Reilly, Manning 和 Packt。它们出版了数量可观的相关图书,但质量良莠不齐,从精心设计和编纂的到搜集科技博客内容整合到一起的都有。


O'Reilly 的机器学习书籍


O'Reilly 的「data」标签下有一百本书,其中大部分都是与机器学习相关的,以下是一些最畅销的书籍。


Programming Collective Intelligence: Building Smart Web 2.0 Applications

地址:http://www.amazon.com/dp/0596529325?tag=inspiredalgor-20


Introduction to Machine Learning with Python: A Guide for Data Scientists

地址:http://www.amazon.com/dp/1449369413?tag=inspiredalgor-20


Deep Learning: A Practitioner's Approach

地址:http://www.amazon.com/dp/1491914254?tag=inspiredalgor-20


Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

地址:http://www.amazon.com/dp/1491925612?tag=inspiredalgor-20


Data Science from Scratch: First Principles with Python

地址:http://www.amazon.com/dp/149190142X?tag=inspiredalgor-20

Python Data Science Handbook: Essential Tools for Working with Data


地址:http://www.amazon.com/dp/1491912057?tag=inspiredalgor-20



Programming Collective Intelligence: Building Smart Web 2.0 Applications 这本书代表了机器学习火热的开始而且已经流行了很长一段时间。


相关链接


O'Reilly 的数据门户

地址:https://www.oreilly.com/topics/data


O'Reilly 的数据产品

地址:http://shop.oreilly.com/category/browse-subjects/data.do 


机器学习初学者工具包:依据数据模式的自动化分析

地址:http://shop.oreilly.com/category/get/machine-learning-kit.do


曼宁机器学习书籍


曼宁的书总是很实用且质量很高,但他们没有类似 O'Reilly 和 Packt 列出的机器学习 100 本书籍的清单。


Machine Learning Action 

地址:http://www.amazon.com/dp/1617290181?tag=inspiredalgor-20


Real-World Machine Learning

地址:http://www.amazon.com/dp/1617291927?tag=inspiredalgor-20


Introducing Data Science:Big Data, Machine Learning, and more, using Python tools

地址:http://www.amazon.com/dp/1633430030?tag=inspiredalgor-20


Practical Data Science with R

地址:http://www.amazon.com/dp/1617291560?tag=inspiredalgor-20


相关链接


曼宁数据科学书籍

地址:https://www.manning.com/catalog#section-68


曼宁机器学习书籍

地址:https://www.manning.com/catalog#section-73


Packt 的机器学习书籍

似乎 Packt 上有所有的数据科学和机器学习的书籍。Packt 有一个大范围的书籍库,库里的书是机器学习方面比较深奥的书籍。同时也有一些当下很流行的机器学习主题的书如 R 语言和 Python。

下面是一些比较流行的书籍。

Machine Learning with R

地址 :http://www.amazon.com/dp/1784393908?tag=inspiredalgor-20

Python Machine Learning

地址:http://www.amazon.com/dp/1783555130?tag=inspiredalgor-20

Practical Machine Learning

地址:http://www.amazon.com/dp/178439968X?tag=inspiredalgor-20

Machine Learning in Java

地址:http://www.amazon.com/dp/1784396583?tag=inspiredalgor-20

Mastering .NET Machine Learning

地址:http://www.amazon.com/dp/1785888404?tag=inspiredalgor-20


其他资源


以下资源是我用来完成本书目所参考的资料,同时也可能是对大家有用的机器学习的额外书单。


亚马逊机器学习最畅销书

链接:http://amzn.to/2iXxccZ


很棒的机器学习书籍

链接:https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md


我是怎样学习机器学习的?Quora 上的回答百科

链接:https://www.quora.com/How-do-I-learn-machine-learning-1


Reddit 的机器学习常见问题与回答

链接:https://www.reddit.com/r/MachineLearning/wiki/index


以上就是目前最为完整的机器学习书目,你读过其中的哪几本?欢迎与大家分享自己的看法。


原文链接:http://machinelearningmastery.com/machine-learning-books/



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