[ COVER OF THE WEEK ]
Big Data knows everything Source
[ LOCAL EVENTS & SESSIONS]
- Apr 26, 2018 #WEB Bottish #7 – All about bots, AI, machine learning & robotics.
- May 30, 2018 #WEB [Webinar] IntroducciÃ³n a DevOps con Jenkins y Docker
- Apr 26, 2018 #WEB ITIL Foundation- 2 days Classroom Training in Chicago
[ AnalyticsWeek BYTES]
[ NEWS BYTES]
[ FEATURED COURSE]
6.867 is an introductory course on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending … more
[ FEATURED READ]
People love statistics. Statistics, however, do not always love them back. The Signal and the Noise, Nate Silver’s brilliant and elegant tour of the modern science-slash-art of forecasting, shows what happens when Big Da… more
[ TIPS & TRICKS OF THE WEEK]
Keeping Biases Checked during the last mile of decision making
Today a data driven leader, a data scientist or a data driven expert is always put to test by helping his team solve a problem using his skills and expertise. Believe it or not but a part of that decision tree is derived from the intuition that adds a bias in our judgement that makes the suggestions tainted. Most skilled professionals do understand and handle the biases well, but in few cases, we give into tiny traps and could find ourselves trapped in those biases which impairs the judgement. So, it is important that we keep the intuition bias in check when working on a data problem.
[ DATA SCIENCE Q&A]
Q:What does NLP stand for?
A: * Interaction with human (natural) and computers languages
* Involves natural language understanding
– Machine translation
– Question answering: whats the capital of Canada?
– Sentiment analysis: extract subjective information from a set of documents, identify trends or public opinions in the social media
– Information retrieval
[ VIDEO OF THE WEEK]
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[ QUOTE OF THE WEEK]
Data is the new science. Big Data holds the answers. Pat Gelsinger
[ PODCAST OF THE WEEK]
[ FACT OF THE WEEK]
140,000 to 190,000. Too few people with deep analytical skills to fill the demand of Big Data jobs in the U.S. by 2018.