5 tips for working with data science interns
sábado, 9 de janeiro de 2016
Back in 2008, there were already more objects connected to the Internet than people
Bernard MarrBernard Marr é um LinkedIn Influencer
Best-Selling Author, Keynote Speaker and Leading Business and Data Expert
Back in 2008, there were already more objects connected to the Internet than people
#IoT #BigData
http://www.forbes.com/sites/bernardmarr/2015/10/27/17-mind-blowing-internet-of-things-facts-everyone-should-read/
How to Present Data to People Who Are Scared of Numbers
by Bernard Marr | November 9, 2015 5:30 am
How to Present Data to People Who Are Scared of Numbers
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How to Present Data to People Who Are Scared of Numbers
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What is Advanced Analytics, Data Science, Machine Learning—and What is their Value?
Kirk Borne @KirkDBorne
5 User-Centered Principles for Designing Data Visualizations | ThoughtWorks
Evan Sinar @EvanSinar
5 User-Centered Principles for Designing Data Visualizations | ThoughtWorks
http://ow.ly/U24e7 #dataviz
5 User-Centered Principles for Designing Data Visualizations | ThoughtWorks
http://ow.ly/U24e7 #dataviz
4 Things Your Data Scientist Should Not Be Doing
4 Things Your Data Scientist Should Not Be Doing
It’s the age of big data. Sets of data so vast, so overwhelming that traditional data processing applications aren’t able to handle them. In fact, according to...
IBM CEO: It is the 'dawn of a new era' where computers think and make decisions
IBM CEO: It is the 'dawn of a new era' where computers think and make decisions
Business Insider India
http://www.businessinsider.in/IBM-CEO-It-is-the-dawn-of-a-new-era-where-computers-think-and-make-decisions/articleshow/49344259.cms
The Industrial Internet of Things (IIoT): Challenges, Requirements and Benefits
Ahmed Banafa
Faculty | Author | Speaker | IoT Expert
The Industrial Internet of Things (IIoT): Challenges, Requirements and Benefits
https://www.linkedin.com/pulse/industrial-internet-things-iiot-challenges-benefits-ahmed-banafa?trk=hp-feed-article-title-share
Faculty | Author | Speaker | IoT Expert
The Industrial Internet of Things (IIoT): Challenges, Requirements and Benefits
https://www.linkedin.com/pulse/industrial-internet-things-iiot-challenges-benefits-ahmed-banafa?trk=hp-feed-article-title-share
Implementación de IPv6: Dual Stack
CISCO CCNA compartilhou originalmente:
Implementación de IPv6: Dual Stack
http://librosnetworking.blogspot.com.ar/2015/11/implementacion-de-ipv6-dual-stack.html
Successful Analytics: Gain Business Insights by Managing Google Analytics
Ronald van Loon @Ronald_vanLoon
Successful Analytics: Gain Business Insights by Managing Google Analytics |#Analytics #GoogleAnalytics #RT http://amzn.to/1JOEscO
Successful Analytics: Gain Business Insights by Managing Google Analytics |#Analytics #GoogleAnalytics #RT http://amzn.to/1JOEscO
Analytics is a Story: Think Like a Writer to Tell It
#bigdata #analytics #evansinar
Analytics is a Story: Think Like a Writer to Tell It
https://www.linkedin.com/pulse/analytics-story-think-like-writer-tell-evan-sinar-phd?trk=hb_ntf_MEGAPHONE_ARTICLE_POST
Analytics is a Story: Think Like a Writer to Tell It
https://www.linkedin.com/pulse/analytics-story-think-like-writer-tell-evan-sinar-phd?trk=hb_ntf_MEGAPHONE_ARTICLE_POST
2015: A Transformative Year for Big Data
2015: A Transformative Year for Big Data
http://data-informed.com/2015-a-transformative-year-for-big-data/
My Brief Guide to Big Data and Predictive Analytics for non-experts
Ronald van Loon @Ronald_vanLoon
My Brief Guide to Big Data and Predictive Analytics for non-experts | #BigData#PredictiveA… http://bit.ly/1N01U9l
My Brief Guide to Big Data and Predictive Analytics for non-experts | #BigData#PredictiveA… http://bit.ly/1N01U9l
UIT cria primeiro padrão oficial para Big Data
UIT cria primeiro padrão oficial para Big Data
http://cio.com.br/tecnologia/2015/12/21/uit-cria-primeiro-padrao-oficial-para-big-data/
http://cio.com.br/tecnologia/2015/12/21/uit-cria-primeiro-padrao-oficial-para-big-data/
Common Errors in Machine Learning due to Poor Statistics Knowledge
Common Errors in Machine Learning due to Poor Statistics Knowledge
Por
Probably the worst error is thinking there is a correlation when that correlation is purely artificial. Take a data set with 100,000 variables, say with 10 observations. Compute all the (99,999 * 100,000) / 2 cross-correlations. You are almost guaranteed to find one above 0.999. This is best illustrated in may article How to Lie with P-values (also discussing how to handle and fix it.)
This is being done on such a large scale, I think it is probably the main cause of fake news, and the impact is disastrous on people who take for granted what they read in the news or what they hear from the government. Some people are sent to jail based on evidence tainted with major statistical flaws. Government money is spent, propaganda is generated, wars are started, and laws are created based on false evidence. Sometimes the data scientist has no choice but to knowingly cook the numbers to keep her job. Usually, these “bad stats” end up being featured in beautiful but faulty visualizations: axes are truncated, charts are distorted, observations and variables are carefully chosen just to make a (wrong) point.
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