教程
====

阅读内容
--------

General Machine Learning

-  Jason’s `Machine Learning
   101 <https://docs.google.com/presentation/d/1kSuQyW5DTnkVaZEjGYCkfOxvzCqGEFzWBy4e9Uedd9k/edit?usp=sharing>`__
   from Google’s Senior Creative Engineer explains Machine Learning for
   engineer’s and executives alike
-  a16z `AI Playbook <https://aiplaybook.a16z.com/>`__ is a great link
   to forward to your managers or content for your presentations
-  `Machine Learning Blog <https://bmcfee.github.io/#home>`__ by Brian
   McFee
-  `Ruder’s Blog <http://ruder.io/#open>`__ by `Sebastian
   Ruder <https://twitter.com/seb_ruder>`__ for commentary on the best
   of NLP Research

Introductions and Guides to NLP

-  Ultimate Guide to `Understand & Implement Natural Language
   Processing <https://www.analyticsvidhya.com/blog/2017/01/ultimate-guide-to-understand-implement-natural-language-processing-codes-in-python/>`__
-  `Introduction to NLP at
   Hackernoon <https://hackernoon.com/learning-ai-if-you-suck-at-math-p7-the-magic-of-natural-language-processing-f3819a689386>`__
   is for people who suck at math - in their own words
-  `NLP Tutorial by Vik
   Paruchari <http://www.vikparuchuri.com/blog/natural-language-processing-tutorial/>`__
-  `Natural Language Processing: An
   Introduction <https://academic.oup.com/jamia/article/18/5/544/829676>`__
   by Oxford
-  `Deep Learning for NLP with
   Pytorch <https://pytorch.org/tutorials/beginner/deep_learning_nlp_tutorial.html>`__
-  `Hands-On NLTK
   Tutorial <https://github.com/hb20007/hands-on-nltk-tutorial>`__ - The
   hands-on NLTK tutorial in the form of Jupyter notebooks

Blogs and Newsletters

-  Blog: `Deep Learning, NLP, and
   Representations <https://colah.github.io/posts/2014-07-NLP-RNNs-Representations/>`__
-  Blog: `The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer
   Learning) <https://jalammar.github.io/illustrated-bert/>`__ and `The
   Illustrated
   Transformer <https://jalammar.github.io/illustrated-transformer/>`__
-  Blog: `Natural Language Processing <https://nlpers.blogspot.com/>`__
   by Hal Daumé III
-  `Tutorials by Radim
   Řehůřek <https://radimrehurek.com/gensim/tutorial.html>`__ on using
   Python and `gensim <https://radimrehurek.com/gensim/index.html>`__ to
   process language corpora
-  `arXiv: Natural Language Processing (Almost) from
   Scratch <https://arxiv.org/pdf/1103.0398.pdf>`__
-  `Karpathy’s The Unreasonable Effectiveness of Recurrent Neural
   Networks <https://karpathy.github.io/2015/05/21/rnn-effectiveness>`__

视频和在线课程
--------------

深度学习和 NLP
~~~~~~~~~~~~~~

Word embeddings, RNNs, LSTMs and CNNs for Natural Language Processing \|

-  Udacity’s `Intro to Artificial
   Intelligence <https://www.udacity.com/course/intro-to-artificial-intelligence--cs271>`__
   course which touches upon NLP as well
-  Udacity’s `Deep
   Learning <https://udacity.com/course/deep-learning--ud730>`__ using
   Tensorflow which covers a section on using deep learning for NLP
   tasks (covering Word2Vec, RNN’s and LSTMs)
-  Oxford’s `Deep Natural Language
   Processing <https://github.com/oxford-cs-deepnlp-2017/lectures>`__
   has videos, lecture slides and reading material
-  Stanford’s `Deep Learning for Natural Language Processing
   (cs224-n) <https://web.stanford.edu/class/cs224n/>`__ by Richard
   Socher and Christopher Manning
-  Coursera’s `Natural Language
   Processing <https://www.coursera.org/learn/language-processing>`__ by
   National Research University Higher School of Economics
-  Carnegie Mellon University’s `Neural Networks for
   NLP <http://phontron.com/class/nn4nlp2017/>`__ by Language Technology
   Institute there

经典 NLP
~~~~~~~~

Bayesian, statistics and Linguistics approaches for Natural Language
Processing \|

-  `Statistical Machine Translation <http://mt-class.org>`__ - a Machine
   Translation course with great assignments and slides
-  `NLTK with Python 3 for Natural Language
   Processing <https://www.youtube.com/playlist?list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL>`__
   by Harrison Kinsley(sentdex). Good tutorials with NLTK code
   implementation
-  `Computational Linguistics
   I <https://www.youtube.com/playlist?list=PLegWUnz91WfuPebLI97-WueAP90JO-15i>`__
   by Jordan Boyd-Graber, Lectures from University of Maryland
-  `Deep NLP Course <https://github.com/yandexdataschool/nlp_course>`__
   by Yandex Data School, covering important ideas from text embedding
   to machine translation including sequence modeling, language models
   and so on.

图书
----

-  `Speech and Language
   Processing <https://web.stanford.edu/~jurafsky/slp3/>`__ by Prof. Dan
   Jurafsy
-  `Text Mining in R <https://www.tidytextmining.com>`__
-  `Natural Language Processing with
   Python <https://www.nltk.org/book/>`__