“Reading Paper”版本间的差异
来自cslt Wiki
（→word vector） |
（→word vector） |
||
| （相同用户的38个中间修订版本未显示） | |||
| 第1行： | 第1行： | ||
| + | ==tool== | ||
| + | * word2vec tool | ||
| + | :* word vector tool for text classification, text clustering or information retrieval[http://sourceforge.net/projects/wvtool/] | ||
| + | :* google word2ve[http://code.google.com/p/word2vec/] | ||
| + | * document vector[http://radimrehurek.com/2014/12/doc2vec-tutorial/?utm_source=rss&utm_medium=rss&utm_campaign=doc2vec-tutorial] | ||
| + | :* genSim[https://github.com/piskvorky/gensim/] new function | ||
| + | * Deep Learning for Java[http://deeplearning4j.org/] | ||
| + | :* word2vec[http://deeplearning4j.org/word2vec.html] | ||
| + | |||
==QA== | ==QA== | ||
[[2014-08-22-qalr]] | [[2014-08-22-qalr]] | ||
| − | + | [[random reading]] | |
| − | + | ||
| − | + | ||
| − | + | ==NN & RNN LM== | |
| − | + | *[[2013-12-3]] | |
| − | 3 | + | *[[2014-8-31]] |
| + | *[[2014-10-9]] | ||
| + | *[[Approaches to convert RNNLM to BNLM]] | ||
| + | ==document classification== | ||
| + | * [[2014-9-10]] | ||
==word vector== | ==word vector== | ||
* [[useful tutorial]] | * [[useful tutorial]] | ||
| + | * [[2014-10-20-word2vec|Learning Word Vectors for Sentiment Analysis]] | ||
| + | * deep learing in nlp | ||
| + | :* distributed representations for compositional semantics [http://arxiv.org/pdf/1411.3146.pdf] | ||
| + | :* Deep Learning for Natural Language Processing and Machine Translation [http://cl.naist.jp/~kevinduh/notes/cwmt14tutorial.pdf] | ||
| + | *Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews[http://arxiv.org/abs/1412.5335] | ||
| + | :*使用RNN和PV在情感分析效果不错,代码[https://github.com/mesnilgr/iclr15] | ||
| + | |||
| + | ==learn report== | ||
| + | [[2014-10-19| basic tasks of speech processing]] | ||
| + | ==learn process== | ||
| + | [[Information Retrieval]] | ||
| + | |||
| + | [[nlp class]] | ||
| + | |||
| + | [[nlp tool]] | ||
==Some Things to remember== | ==Some Things to remember== | ||
| − | * | + | * video lectures [http://videolectures.net/] |
| + | * free books [http://www.justfreebooks.info/] | ||
| + | * 推荐系统的tutorial slides [http://alex.smola.org/teaching/berkeley2012/slides/8_Recommender.pdf][http://www.slideshare.net/xamat/recommender-systems-machine-learning-summer-school-2014-cmu] | ||
| + | * understanding-lbfgs [http://aria42.com/blog/2014/12/understanding-lbfgs/] | ||
| + | * ml blog[http://www.cs.waikato.ac.nz/~bernhard/good-machine-learning-blogs.html][http://www.quora.com/What-are-the-best-machine-learning-blogs-or-resources-available] | ||
| + | * 公开课[http://52opencourse.com/] | ||
| + | * 机器学习日报[http://ml.memect.com/] | ||
| + | :* 包含大量的学习资源 | ||
| + | * Advanced Machine Learning[http://www.seas.harvard.edu/courses/cs281/] | ||
2014年12月29日 (一) 07:58的最后版本
目录
tool
- word2vec tool
- document vector[3]
- genSim[4] new function
- Deep Learning for Java[5]
- word2vec[6]
QA
NN & RNN LM
document classification
word vector
- useful tutorial
- Learning Word Vectors for Sentiment Analysis
- deep learing in nlp
- Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews[9]
- 使用RNN和PV在情感分析效果不错,代码[10]
learn report
basic tasks of speech processing
learn process
Some Things to remember
- video lectures [11]
- free books [12]
- 推荐系统的tutorial slides [13][14]
- understanding-lbfgs [15]
- ml blog[16][17]
- 公开课[18]
- 机器学习日报[19]
- 包含大量的学习资源
- Advanced Machine Learning[20]
