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  

4 Things Your Data Scientist Should Not Be Doing

4 Things Your Data Scientist Should Not Be Doing

• AjayPaghdal
 
• September 15, 2016 at 3:30 pm

  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...

https://www.datasciencecentral.com/4-things-your-data-scientist-should-not-be-doing/

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

Are operating systems and applications your main cybersecurity focuses?

Intel Security compartilhou originalmente:

 

Are operating systems and applications your main cybersecurity focuses? 

You may need to add a few more to the list: http://intel.ly/1HnLRAg 

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

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

Big Data, Smaller Risk

#bigdata     Big Data, Smaller Risk
http://ww2.cfo.com/big-data-technology/2015/10/big-data-smaller-risk/

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

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  

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/

Common Errors in Machine Learning due to Poor Statistics Knowledge

Common Errors in Machine Learning due to Poor Statistics Knowledge

Por 

 Vincent Granville  -  

July 2, 2020 at 4:48 am

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.

Read the full article here. 

https://www.datasciencecentral.com/common-errors-in-machine-learning-due-to-poor-statistics-knowledg-2/



Announcing a New Free Primer on Web Analytics | Web Analytics Action Hero

Announcing a New Free Primer on Web Analytics | Web Analytics Action Hero

analyticshero.com

http://www.analyticshero.com/2014/10/02/announcing-a-new-free-primer-on-web-analytics/