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Ask HN: What journals and blogs should I be reading to become a data scientist?

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Re: Ask HN: What journals and blogs should I be reading to become a data scientist?

#3
post #2

http://www.informationisbeautiful.net/ http://blog.okcupid.com/ https://www.facebook.com/data/ http://www.pornhub.com/insights/

A recently launched HN style community [0] is pretty good as well

[0] http://www.datatau.com/news

Re: Ask HN: What journals and blogs should I be reading to become a data scientist?

#5
Becoming a data scientist isn't a matter of reading journals and blogs. You can get a sense of the field and what is required by reading those sites but becoming a data scientist is years of hard work.

You need to develop serious skills in at least 4 of the following disciplines. Statistical analysis

RDMS query development

NoSQL databases

Machine learning

Natural Language Processing

Web crawling and data harvesting techniques

Programming to access data APIs

Web development

Data visualization

Systems in business that generate data including, CRM, ERP and more

Geospatial data systems

Each of these areas would have its own set of resources both formal and informal.

Re: Ask HN: What journals and blogs should I be reading to become a data scientist?

#6
Subscribe to Data Science Weekly: http://www.datascienceweekly.org/

http://blog.zipfianacademy.com/

http://blog.cloudera.com/blog/category/data-science/

http://www.hilarymason.com/

http://mathbabe.org/

http://fivethirtyeight.blogs.nytimes.com/

http://blog.kaggle.com/

http://grepalex.com/

http://pulseblog.emc.com/category/big-data/

http://radar.oreilly.com/

http://flowingdata.com/

http://oreilly.com/data/newsletter.html

http://www.gapminder.org/

http://mlcomp.org/

Re: Ask HN: What journals and blogs should I be reading to become a data scientist?

#10
You know, I absolutely see where the poster is coming from, and the suggestions look helpful so far, but the question might as well read: What journals and blogs should I be reading to become a Cardiothoracic Surgeon?

(though hopefully nobody bleeds out on a table when someone misconstrues statistical data)

We've lived through an amazing time where one could learn by doing, and talented people have been able to compete without the benefit of formal education (myself included), but in my opinion those days are numbered.

I've personally observed respected PhD statisticians stumble on the type of problems a data scientist is expected to address. The combination of complex software and often counterintuitive mathematics makes this an imposing field for all but perhaps the top one percent of practitioners. Most everybody else needs to really hit the books for a few years, in a formal setting.

With that pre-coffee rant out of the way, I'm looking forward to finding some new sources here myself. So, in that spirit, thanks for the question.

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