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Data Scientist TJO in Tokyo

Data science, statistics or machine learning in broken English

data science

In Japan, now "Artificial Intelligence" comes to be a super star, while "Data Scientist" has been forgotten

Almost two years ago, I wrote a post about the situation of "Data Scientist" and "Artificial Intelligence" at that time.After two years have passed, now what's happening and what do we see? Below is a summary of current situation of data s…

Can multivariate modeling predict taste of wine? Beyond human intuition and univariate reductionism

Taste of Wine vs. Data Science from Takashi J OZAKI At a certain meetup on the other day, I talked about a brand-new relationship between taste of wine (i.e. professional tasting) and data science. This talk was inspired by a book "Wine Sc…

In Japan "Data Scientist" has gone and "Artificial Intelligence" is explosively rising

More than a year ago, I pointed out that "Data Scientist" has attracted less attention than ever.Puzzling situation of "Data Scientist" in Japanese market - Data Scientist in Ginza, TokyoSo, what's going on in 2015?... yes, I think not a f…

What kind of decision boundaries does Deep Learning (Deep Belief Net) draw? Practice with R and {h2o} package

For a while (at least several months since many people began to implement it with Python and/or Theano, PyLearn2 or something like that), nearly I've given up practicing Deep Learning with R and I've felt I was left alone much further away…

Visualizing supervised machine learning with association rules and graphical modeling

On Apr 17, I joined Global TokyoR #1 and talked about a stuff below. Visualization of Supervised Learning with {arules} + {arulesViz} from Takashi J Ozaki (Note: please install {igraph} package before installing {arulesViz}) By the way, th…

Answers to "10 questions about big data and data science" from Japan

I read a set of much interesting questions by Dr. Vincent Graville as below: 10 questions about big data and data science - Data Science Central Should companies embrace big data? Which ones (start-ups, big-companies, tech companies, retai…