Stanford University CS224d: Deep Learning for Natural Language Processing

http://cs224d.stanford.edu/

Through lectures and programming assignments students will learn the necessary engineering tricks for making neural networks work on practical problems.

http://cs224d.stanford.edu/syllabus.html

Variant tf-idf functions | Introduction to Information Retrieval

http://nlp.stanford.edu/IR-book/html/htmledition/variant-tf-idf-functions-1.html

For assigning a weight for each term in each document, a number of alternatives to tf and tf-idf have been considered.

GloVe: Global Vectors for Word Representation

http://nlp.stanford.edu/projects/glove/

GloVe is an unsupervised learning algorithm for obtaining vector representations for words. Training is performed on aggregated global word-word co-occurrence statistics from a corpus, and the resulting representations showcase interesting linear substructures of the word vector space.

Stanford University CS231n: Course Projects Winter 2015

http://cs231n.stanford.edu/reports.html

CS231n: Convolutional Neural Networks for Visual Recognition

CS231n Course Project Reports

Unsupervised Feature Learning and Deep Learning Tutorial

http://ufldl.stanford.edu/tutorial/

Description: This tutorial will teach you the main ideas of Unsupervised Feature Learning and Deep Learning.

ディープ・ラーニングだけではなく、多層ニューラルネットなどの基礎技術の解説もある。

Stanford University CS231n: Convolutional Neural Networks for Visual Recognition

http://vision.stanford.edu/teaching/cs231n/