Turing Shield (@TuringShield) profile picture

Lead GenAI Solution Architect

Joined June 2011
If machine learning were a human, then soul is math & stats, body is algorithm & data structure, blood is #data. Coding connect all together
11
275
17
261
Mostly accuracy. The potential for scalability is also important.
1
1
If your project's success depends heavily on performance of Named Entity Recognition, please start with OpenNLP. Be aware that NER's results are highly domain specific. If your textual data is very different from the training data OpenNLP or StanfordNLP used, train your own model
3
2
If your project heavily depends on Named Entity Recognition, I recommend investing time with OpenNLP first
2
What was the false-negative rate? thanks
#AI has a lot of potentials in specialized areas in health informatica, ,but is still very limited in many areas.
1
Replying to @TheEconomist
It is an interesting read. It reminds of the anecdotal 10,000-rule, as described in Outliers by @Gladwell
1
Success in the sciences does not always breed more success econ.st/2Vujy5p
1
49
3
145
News & Views: A paper in Nature outlines an approach that brings us closer to a brain–computer interface that can restore speech function. go.nature.com/2UXgHRS
3
58
4
143
Replying to @thealexfreeman
Another great analogy!
1
Named entity recognition is easy for humans and hard for machines. Correctly recognizing brands, companies and services is critical in marketing research that uses textual #bigdata. CoreNLP by @stanfordnlp fulfills several advertising research needs well: stanfordnlp.github.io/CoreNL…
1
20
52
Jack Ma of @AlibabaGroup believes that Artificial Intelligence threatens human beings: businesstoday.in/technology/…. Jack's points seem to be at odds with some of top #AI and machine learning researchers in #bigdata.
3
The power of machine learning in healthcare analytics: the potential value of big data in predicting, preventing and curing disease. Precision health: scopeblog.stanford.edu/2018/…
Natural language processing (#NLP) is a subfield in artificial intelligence (#AI). Many #MachineLearning approaches are available for #NLP. #NLP is useful in analysis of #bigdata, augmented reality (#AR) and #IoT: medium.com/@Namenode5/the-ne….
1
8
Turing Shield retweeted
We need a Goldilocks Rule for AI: - Too optimistic: Deep learning gives us a clear path to AGI! - Too pessimistic: DL has limitations, thus here's the AI winter! - Just right: DL can’t do everything, but will improve countless lives & create massive economic growth. – at Palo Alto, CA
47
926
72
2,909
Two machine learning methods for sentiment analysis are useful. One is #DeepLearning, for which @stanfordnlp provides a Java implementation nlp.stanford.edu/sentiment/. Another is #MaxEnt, i.e., maximum entropy, a good classifier for textual #bigdata of brand user generated content.
29
89
Interesting points, well taken.