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If machine learning were a human, then soul is math & stats, body is algorithm & data structure, blood is #data. Coding connect all together
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Success in the sciences does not always breed more success econ.st/2Vujy5p
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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
The dark side of artifiical intelligence: Researchers create 'malicious' writing AI bbc.com/news/technology-4724…
Big Four accounting companies invest huge in artificial intelligence: (old news, but still current): computerworld.com/article/30…
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…
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.
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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….
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How do algorithms and bots affect election outcomes? New paper on automated political communication in the 2016 US election out now in the Journal of Information Technology and Politics! Read on: tandfonline.com/doi/full/10.… @pnhoward @samuelwoolley #TechNews #politics
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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
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.
Mastering unstructured #bigdata with machine learning and natural language processing (#NLP). #Java, #Python, @Stata, #R etc.. I use a Java-based tool by @stanfordnlp. Its deep learning for sentiment analysis is useful: stanfordnlp.github.io/CoreNL…. Note @scikit_learn is in #python
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Yesterday, Chair of Morgan Stanley’s Quantitative Council Marty Leibowitz sat down with Andrew Lo, Director of the MIT Laboratory for Financial Engineering, to speak about the future of quant and how fundamental research continues to be enhanced by AI and machine learning.
Chatbots, when enabled by artificial intelligence (#AI) and machine learning, will be extremely helpful for certain industries in the age of #Bigdata: ibm.com/blogs/watson/2017/05…
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Our new Online #Banking Report is out! Discover the latest trends and behavioral patterns impacting the banking sector in Europe: ow.ly/xnq430kuZx0.
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Workers may have to choose between being replaced by a robot or being treated like one econ.st/2sWGbyX
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Imagine seamlessly visiting any place in the world from your home - with #5G you can! Visit us at #5GWorld and experience the historical Pietro Micca Museum using #virtualreality. m.eric.sn/8QPE30kukqh










