任何階段的學習者都適用的參考:機器學習領域書目全集

張貼者:2017年1月16日 下午9:36marketing Honghu   [ 已更新 2017年1月16日 下午9:36 ]

來自Swinburne 科技大學的JasonBrownlee 博士為我們帶來了最新一期的機器學習書目,內容覆蓋科普、各級教材以及不同編程語言的機器學習應用。

 

原文來源:來源:http://machinelearningmastery.com/machine-learning-books/

 

學習是一種理性的投資,每當花費十幾個小時讀完一本書,你就能領略到前人數年積累的經驗。

 

在閱讀了市面上大多數機器學習書籍後,作者列出了最新機器學習領域推薦圖書,並使用了使用不同分類方式進行了整理:

按類型:教科書,熱門學科等;

按主題:Python,深度學習等;

按出版商:PacktO'Reilly 等;

……

 

如何使用

1. 找到你最感興趣的分類方式,找到需要的主題;

2. 在你選擇的主題中挑選;

3. 購買圖書;

4. 從頭到尾閱讀;

5. 繼續找下一本。

 

擁有一本書和了解它的內容是完全不同的兩種概念——你必須真正閱讀它們。

請先問問自己:你有沒有讀完過一本機器學習的書?

 

機器學習圖書——按類型分

最流行機器學習科普圖書

以下圖書適用於大多數讀者。它們點到了機器學習和數據科學的精華之處,卻沒有使用枯燥的理論或應用細節。這份書單也包括了一些流行的「統計思想」科普書籍。

 

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

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


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

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


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

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


Naked Statistics: Stripping the Dread fromthe Data

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


The Drunkard's Walk: How Randomness RulesOur Lives

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



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

適用於機器學習初學者的書籍

以下列出最適用於初學者的書籍。希望入門的讀者同時也需要參考科普圖書(上一條)以及行業應用圖書(下一條)。


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

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


Data Smart: Using Data Science to TransformInformation into Insight

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


Data Mining: Practical Machine LearningTools and Techniques

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


Doing Data Science: Straight Talk from theFrontline

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



在這其中最重要的一本是:《Data Mining: PracticalMachine Learning Tools and Techniques》。

機器學習入門書籍——高級


以下是適用於希望入門機器學習的本科學生和開發者的書籍,內容包含了機器學習的很多話題,注重如何解決問題,而不是介紹理論。


Machine Learning for Hackers: Case Studiesand 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



其中最值得推薦的一本是:《An Introduction toStatistical Learning: with Applications in R

機器學習教材

以下列出了機器學習領域目前最流行的教科書。它們會在研究生課程中出現,包含方法與理論的解讀。

The Elements of Statistical Learning: DataMining, 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 ProbabilisticPerspective

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 ofAlgorithms 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



其中的重點是:《The Elements of StatisticalLearning: Data Mining, Inference, and Prediction

機器學習圖書——按主題分


有關語言在機器學習中如何應用的圖書。

The Elements of Statistical Learning: DataMining, 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 ProbabilisticPerspective

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 ofAlgorithms 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


這方面的首選圖書是:《The Elements of StatisticalLearning: Data Mining, Inference, and Prediction》。


Python 機器學習

以下列出Python 機器學習熱門書籍

Python Machine Learning

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


Data Science from Scratch: First Principleswith Python

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


Hands-On Machine Learning with Scikit-Learnand TensorFlow: Concepts, Tools, and Techniques for Building IntelligentSystems

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


Introduction to Machine Learning withPython: A Guide for Data Scientists

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


Vital Introduction to Machine Learning withPython: Best Practices to Improve and Optimize Machine Learning Systems andAlgorithms

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


Machine Learning in Python: EssentialTechniques for Predictive Analysis

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


Python Data Science Handbook: EssentialTools for Working with Data

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


Introducing Data Science: Big Data, MachineLearning, 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



最值得注意的當然是《Python 機器學習》了。

深度學習

注意:深度學習的圖書目前還比較稀缺,以下這份列表只能保證數量,而不是質量。

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: DesigningNext-Generation Machine Intelligence Algorithms

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


Learning TensorFlow: A guide to buildingdeep 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-OnIntroduction to Learning Algorithms

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



其中最重要的一本書當然是:Yoshua Bengio Ian Goodfellow 所著的《Deep Learning》。

時序序列預測

目前時序序列預測在實際應用中主要是由語言的平台所主導。

Time Series Analysis: Forecasting andControl

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

Practical Time Series Forecasting with R: AHands-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

Forecastingprinciplesand practice

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

 


最優質的入門介紹書籍是Forecastingprinciples and practice

時序序列最優質的教科書是Time Series Analysis:Forecasting and Control


機器學習圖書——按照出版商分類

目前活躍在機器學習領域的出版商主要有: O'Reilly, Manning Packt。它們出版了數量可觀的相關圖書,但質量良莠不齊,從精心設計和編纂的到蒐集科技博客內容整合到一起的都有。


O'Reilly 的機器學習書籍


O'Reilly 的「data」標籤下有一百本書,其中大部分都是與機器學習相關的,以下是一些最暢銷的書籍。

Programming Collective Intelligence:Building Smart Web 2.0 Applications

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


Introduction to Machine Learning withPython: 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: DesigningNext-Generation Machine Intelligence Algorithms

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


Data Science from Scratch: First Principleswith Python

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


Python Data Science Handbook: EssentialTools for Working with Data

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


Programming Collective Intelligence:Building Smart Web 2.0 Applications 這本書代表了機器學習火熱的開始而且已經流行了很長一段時間。

相關鏈接

O'Reilly 的數據門戶

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


O'Reilly 的數據產品

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


機器學習初學者工具包:依據數據模式的自動化分析

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


曼寧機器學習書籍

曼寧的書總是很實用且質量很高,但他們沒有類似O'Reilly Packt 列出的機器學習100 本書籍的清單。

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 ScienceBig 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


相關鏈接

曼寧數據科學書籍

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


曼寧機器學習書籍

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


Packt 的機器學習書籍

似乎Packt 上有所有的數據科學和機器學習的書籍。Packt 有一個大範圍的書籍庫,庫裡的書是機器學習方面比較深奧的書籍。同時也有一些當下很流行的機器學習主題的書如語言和Python


下面是一些比較流行的書籍。

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


其他資源

以下資源是我用來完成本書目所參考的資料,同時也可能是對大家有用的機器學習的額外書單。

亞馬遜機器學習最暢銷書

鏈接:http://amzn.to/2iXxccZ


很棒的機器學習書籍

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


我是怎樣學習機器學習的?Quora 上的回答百科

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


Reddit 的機器學習常見問題與回答

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


以上就是目前最為完整的機器學習書目,你讀過其中的哪幾本?歡迎與大家分享自己的看法。

 

 

來源:http://machinelearningmastery.com/machine-learning-books/

 

台灣最大人工智能、深度學習與GPU議題社團,採實名制,歡迎申請加入

https://www.facebook.com/groups/marketing.gpu


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