Deep Learning can be used to automate just about every repetitive task that is currently or formerly performed by humans. Factory robots, autonomous cars, Internet of Things are example of these automations. Yet, mentally challenging tasks such as conducting research or strategic planning with natural language textual documents remain a daunting task for automation. We look into the root cause of this challenge and have implemented a solution to automate these…Continue
Added by Sing Koo on October 6, 2017 at 1:00pm — No Comments
Prevailing AI technology for analytics prefer the use of statistical science as the foundation for machine learning (ML) on historical data to distill knowledge and experience. Whether it be supervised or unsupervised, the result is then incorporated into playback engines to analyze new data. These methods and procedures work well for predictable scenarios with known outcomes and known variables.
What if the variables are unknown, and…Continue
Added by Sing Koo on May 19, 2017 at 9:00am — No Comments
If you’re relatively new to the NLP and Text Analysis world, you’ll more than likely have come across some pretty technical terms and acronyms, that are challenging to get your head around, especially, if you’re relying on scientific definitions for a plain and simple explanation.
We decided to put together a list of 10 common terms in Natural Language Processing which we’ve broken down in layman terms, making them easier to understand. So if you don’t know your “Bag of Words”…Continue
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