4.3.4. 教程

4.3.4.1. 阅读内容

General Machine Learning

• Jason’s Machine Learning 101 from Google’s Senior Creative Engineer explains Machine Learning for engineer’s and executives alike

• a16z AI Playbook is a great link to forward to your managers or content for your presentations

• Machine Learning Blog by Brian McFee

• Ruder’s Blog by Sebastian Ruder for commentary on the best of NLP Research

Introductions and Guides to NLP

• Ultimate Guide to Understand & Implement Natural Language Processing

• Introduction to NLP at Hackernoon is for people who suck at math - in their own words

• NLP Tutorial by Vik Paruchari

• Natural Language Processing: An Introduction by Oxford

• Deep Learning for NLP with Pytorch

• Hands-On NLTK Tutorial - The hands-on NLTK tutorial in the form of Jupyter notebooks

Blogs and Newsletters

• Blog: Deep Learning, NLP, and Representations

• Blog: The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer Learning) and The Illustrated Transformer

• Blog: Natural Language Processing by Hal Daumé III

• Tutorials by Radim Řehůřek on using Python and gensim to process language corpora

• arXiv: Natural Language Processing (Almost) from Scratch

• Karpathy’s The Unreasonable Effectiveness of Recurrent Neural Networks

4.3.4.2. 视频和在线课程

4.3.4.2.1. 深度学习和 NLP

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

• Udacity’s Intro to Artificial Intelligence course which touches upon NLP as well

• Udacity’s Deep Learning 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 has videos, lecture slides and reading material

• Stanford’s Deep Learning for Natural Language Processing (cs224-n) by Richard Socher and Christopher Manning

• Coursera’s Natural Language Processing by National Research University Higher School of Economics

• Carnegie Mellon University’s Neural Networks for NLP by Language Technology Institute there

4.3.4.2.2. 经典 NLP

Bayesian, statistics and Linguistics approaches for Natural Language Processing |

• Statistical Machine Translation - a Machine Translation course with great assignments and slides

• NLTK with Python 3 for Natural Language Processing by Harrison Kinsley(sentdex). Good tutorials with NLTK code implementation

• Computational Linguistics I by Jordan Boyd-Graber, Lectures from University of Maryland

• Deep NLP Course by Yandex Data School, covering important ideas from text embedding to machine translation including sequence modeling, language models and so on.

4.3.4.3. 图书

• Speech and Language Processing by Prof. Dan Jurafsy

• Text Mining in R

• Natural Language Processing with Python