機器學習、深度學習與自然語言處理領域推薦的書籍列表

https://segmentfault.com/a/1190000008598352

機器學習

• 2007 - Pattern Recognition And Machine Learning【Book】 : The book is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.
• 2012 - Machine Learning A Probabilistic Perspective 【Book】 : This textbook offers a comprehensive and self-contained introduction to the field of machine learning, a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability , optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning.
• 2012 -李航:統計方法學：李航老師的這本書偏優化和推倒，推倒相應算法的時候可以參考這本書。
• 2014 - DataScience From Scratch【Book】 : In this book, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.
• 2015 - Python Data Science Handbook【Book】 :Jupyter Notebooks for the Python Data Science Handbook
• 2015 - Data Mining, The Textbook【Book】 : This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues.
• 2016 -周志華機器學習【Book】：周志華老師的這本書非常適合作為機器學習入門的書籍，書中的例子十分形象且簡單易懂。
• University of Illinois at Urbana-Champaign:Text Mining and Analytics【Course】
• 台大機器學習技法【Course】
• 斯坦福機器學習課程【Course】
• CS224d: Deep Learning for Natural Language Processing【Course】
• Unsupervised Feature Learning and Deep Learning【Course】 :來自斯坦福的無監督特徵學習與深度學習系列教程
• 史上最全的机器学习资料（下）涵蓋24種編程語言的機器學習的框架、庫以及其他相關資料https://my.oschina.net/freegodly/blog/740027 

深度學習

• 2015-The Deep Learning Textbook【Book】 :中文譯本這裡，The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free.
• Stanford Deep Learning Tutorial【Book】 : This tutorial will teach you the main ideas of Unsupervised Feature Learning and Deep Learning. By working through it, you will also get to implement several feature learning/deep learning algorithms, get to see them work for yourself , and learn how to apply/adapt these ideas to new problems.
• Neural Networks and Deep Learning【Book】 : Neural Networks and Deep Learning is a free online book. The book will teach you about: (1) Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data. (2) Deep learning, a powerful set of techniques for learning in neural networks
• Practical Deep Learning For Coders 【Course】 :七週的免費深度學習課程，學習如何構建那些優秀的模型。
• Oxford Deep NLP 2017 course【Course】 : This is an advanced course on natural language processing. Automatically processing natural language inputs and producing language outputs is a key component of Artificial General Intelligence.

自然語言處理

• 2016 - CS224d: Deep Learning for Natural Language Processing【Course】
• 2017 - Oxford Deep NLP 2017 course【Course】
• [2015 - Text Data Management and Analysis【Book】](): A Practical Introduction to Information Retrieval and Text Mining
• DL4NLP-Deep Learning for NLP resources【Resource】

NLP survy

Gate-vs-UIMA-vs-OpenNLP
https://app.assembla.com/spaces/extraction-of-cost-data/wiki/Gate-vs-UIMA-vs-OpenNLP

NLP相關資源
https://handong1587.github.io/deep_learning/2015/10/09/nlp.html

NLP 笔记--徐阿衡

http://www.shuang0420.com/categories/NLP/

NLP 笔记 - Sentiment Analysis
06-01
论文笔记 - Learning to Extract Conditional Knowledge for Question Answering using Dialogue
05-24
NLP 笔记 - Text Summarization
05-10
NLP 笔记 - Machine Translation
05-01
NLP笔记 - NLU之意图分类
04-27
NLP 笔记 - Compositional Semantics
04-13
NLP笔记 - Relation Extraction


Deep Learning for NLP course
oxford: https://github.com/oxford-cs-deepnlp-2017/lectures

The course provides a deep excursion into cutting-edge research in deep learning applied to NLP. The final project will involve training a complex recurrent neural network and applying it to a large scale NLP problem.
http://cs224d.stanford.edu/syllabus.html
http://cs224d.stanford.edu/

How to Generate a Good Word Embedding? (source code)
Folder embedding contains all embedding algorithms we used in this paper.

Folder evaluation contains all evaluation tasks in the paper.
https://github.com/licstar/compare

Blog文章

• Deep Learning in NLP
• 维基百科简体中文语料的获取
• 《How to Generate a Good Word Embedding?》导读

http://licstar.net/archives/category/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86

Using NLP, Machine Learning & Deep Learning Algorithms to Extract Meaning from Text
https://www.infoq.com/presentations/nlp-machine-learning-meaning-text

NLP频道
https://liweinlp.com/?p=29
http://blog.sciencenet.cn/blog-362400-902391.html

立委博士，自然語言處理（NLP）資深架構師，Pinciple Scientist, jd-valley, Netbase前首席科學家，期間指揮團隊研發了18種語言的理解和應用系統。特別是漢語和英語，具有世界一流的分析（parsing）精度，並且做到魯棒、線速，scale up to大數據，語義落地到數據挖掘和問答產品。Cymfony前研發副總，曾榮獲第一屆問答系統第一名（TREC-8 QA Track），並贏得17個美國國防部的信息抽取項目（PI for 17 SBIRs）。立委NLP工作的應用方向包括大數據輿情挖掘、客戶情報、信息抽取、知識圖譜、問答系統、智能助理、語義搜索等等。

Introduction to NLP Architecture
https://www.linkedin.com/pulse/introduction-nlp-architecture-wei-li
   

Introduction to Natural Language Processing (NLP) 2016
The field of study that focuses on the interactions between human language and computers is called Natural Language Processing, or NLP for short. 
http://blog.algorithmia.com/introduction-natural-language-processing-nlp/