Difference between revisions of "List of Relevant Blogs and Feeds"
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== Frequently about NLP == | == Frequently about NLP == | ||
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* [http://datamining.typepad.com/data_mining/ Data Mining: Text Mining, Visualization and Social Media] | * [http://datamining.typepad.com/data_mining/ Data Mining: Text Mining, Visualization and Social Media] | ||
| − | = Machine Learning / Stats / Information Retrieval | + | = Machine Learning / Stats / Information Retrieval = |
* [http://blog.smola.org Adventures in Data Land] [ http://blog.smola.org/rss (RSS Feed)] - Alex Smola breaks down concepts often obscured in scientific papers | * [http://blog.smola.org Adventures in Data Land] [ http://blog.smola.org/rss (RSS Feed)] - Alex Smola breaks down concepts often obscured in scientific papers | ||
* [http://behind-the-enemy-lines.blogspot.com/ A Computer Scientist in Business School] - Panos Ipeirotis often writes about building models using crowdsourcing resources like The Amazon Mechanical Turk | * [http://behind-the-enemy-lines.blogspot.com/ A Computer Scientist in Business School] - Panos Ipeirotis often writes about building models using crowdsourcing resources like The Amazon Mechanical Turk | ||
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* [http://www.machinedlearnings.com Machined Learnings] - Paul Minero some pretty theoretical posts that pertain to his job at eHarmony. | * [http://www.machinedlearnings.com Machined Learnings] - Paul Minero some pretty theoretical posts that pertain to his job at eHarmony. | ||
* [http://www.stat.columbia.edu/~gelman/blog/ Statistical Modeling, Causal Inference, and Social Science] - Statistician Andrew Gelman writes about everything in this blog's title. | * [http://www.stat.columbia.edu/~gelman/blog/ Statistical Modeling, Causal Inference, and Social Science] - Statistician Andrew Gelman writes about everything in this blog's title. | ||
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Revision as of 17:27, 10 October 2010
NLP
Frequently about NLP
- NLPers (RSS Feed) - Hal Daume, Assistant Professor writes his musings about NLP, his research. His conference overviews are a great way to build a suggested reading list.
- LingPipe Blog (RSS Feed) - Bob Carpenter writes detailed posts often about NLP techniques that get integrated into his LingPipe software. Be sure to check out his blog roll.
- Computational Linguistics (RSS Feed) - This feed is a handy way to keep on top of the latest journal articles in our field.
- Journal of Natural Language Engineering (RSS Feed) - A feed from another prestigious journal in NLP
- CFPs on NLP (RSS Feed) - Use this to get the latest updates on calls for papers/participation from NLP related conferences
Occasionally about NLP
- The Language Log (RSS Feed) - Weblog run by University of Pennsylvania phonetician Mark Liberman, with multiple guest linguists.
- The LINGUIST List (RSS Feed) - An e-mail list with information relating to all manners of linguistics. This is a good place to hunt for post-doc or academic job opportunities.
- Data Mining: Text Mining, Visualization and Social Media
Machine Learning / Stats / Information Retrieval
- Adventures in Data Land [ http://blog.smola.org/rss (RSS Feed)] - Alex Smola breaks down concepts often obscured in scientific papers
- A Computer Scientist in Business School - Panos Ipeirotis often writes about building models using crowdsourcing resources like The Amazon Mechanical Turk
- The Noisy Channel (RSS Feed) - Googler Daniel Tunkelang talks about machine learning, information theory, social networks, etc...
- Machined Learnings - Paul Minero some pretty theoretical posts that pertain to his job at eHarmony.
- Statistical Modeling, Causal Inference, and Social Science - Statistician Andrew Gelman writes about everything in this blog's title.
Etc
- PhD Comics (RSS Feed) - A surprisingly accurate portrayal of grad school told in comic form.
- Peter Norvig (RSS Feed) - Jim's grad school colleague, and director of Google research writes a delightful blog with entries like the Gettysburg Address in Powerpoint or The World's Longest Palindrome Sentence.
- OKTrends - The official blog from OK Cupid is chock full of fun data mining and visualizations about dating and love.
