Originally posted here, where you can see all the graphics.
There has been much in the news lately about the next wave of MT technology driven by a technology called deep learning and neural nets (DNN). I will attempt to provide a brief layman’s overview about what this is, even though I am barely qualified to do this (but if Trump can run for POTUS then…Continue
Added by Kirti Vashee on July 29, 2016 at 9:30am — No Comments
Text classification (a.k.a. text categorization) is one of the most prominent application of Machine Learning. The purpose of text classification is to give conceptual organization to large collection of documents.An interesting application of text classification is to categorize research papers by most suitable conferences. Finding and selecting a suitable academic conference has always been a challenging task especially for…Continue
Added by Aqib Saeed on July 26, 2016 at 3:04am — No Comments
Sentiment analysis is hard. Most of the systems on the market will clock anywhere around 55-65% for unseen data, even though they might be 85%+ accurate in their cross-validations.
A couple of reasons why creating a generic sentiment analyser is tough;
- There is too much variation in texts across domains, leading to different meanings
- Identifying sarcasm and combination of phrases like, 'not bad' is not equal to 'not' AND 'bad'
This blog post was originally published as part of an ongoing series, "Popular Algorithms Explained in Simple English" on the AYLIEN Text Analysis Blog.
Picture added by the…Continue
Any author would like to know if his/her article will be successful or not. Here is an attempt to deal with this task.
Data and tools
Summary: Gartner says that predictive analytics is a mature technology yet only one company in eight is currently utilizing this ability to predict the future of sales, finance, production, and virtually every other area of the…Continue
Added by William Vorhies on August 13, 2014 at 10:54am — No Comments