Jan 31, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)

[  COVER OF THE WEEK ]

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Convincing  Source

[ LOCAL EVENTS & SESSIONS]

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> Data Science is more than Machine Learning  by analyticsweek

>> The Upper Echelons of Cognitive Computing: Deriving Business Value from Speech Recognition by jelaniharper

>> Talend and Splunk: Aggregate, Analyze and Get Answers from Your Data Integration Jobs by analyticsweekpick

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[ NEWS BYTES]

>>
 Regulating the Internet of Things – RFID Journal Under  Internet Of Things

>>
 Analytics Use Grows in Parallel with Data Volumes – Datanami Under  Analytics

>>
 Startup right in 2019: how to set up your customer experience for success – SmartCompany.com.au Under  Customer Experience

More NEWS ? Click Here

[ FEATURED COURSE]

Process Mining: Data science in Action

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Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be ap… more

[ FEATURED READ]

Introduction to Graph Theory (Dover Books on Mathematics)

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A stimulating excursion into pure mathematics aimed at “the mathematically traumatized,” but great fun for mathematical hobbyists and serious mathematicians as well. Requiring only high school algebra as mathematical bac… more

[ TIPS & TRICKS OF THE WEEK]

Save yourself from zombie apocalypse from unscalable models
One living and breathing zombie in today’s analytical models is the pulsating absence of error bars. Not every model is scalable or holds ground with increasing data. Error bars that is tagged to almost every models should be duly calibrated. As business models rake in more data the error bars keep it sensible and in check. If error bars are not accounted for, we will make our models susceptible to failure leading us to halloween that we never wants to see.

[ DATA SCIENCE Q&A]

Q:You are compiling a report for user content uploaded every month and notice a spike in uploads in October. In particular, a spike in picture uploads. What might you think is the cause of this, and how would you test it?
A: * Halloween pictures?
* Look at uploads in countries that don’t observe Halloween as a sort of counter-factual analysis
* Compare uploads mean in October and uploads means with September: hypothesis testing

Source

[ VIDEO OF THE WEEK]

@AnalyticsWeek #FutureOfData with Robin Thottungal(@rathottungal), Chief Data Scientist at @EPA

 @AnalyticsWeek #FutureOfData with Robin Thottungal(@rathottungal), Chief Data Scientist at @EPA

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[ QUOTE OF THE WEEK]

It is a capital mistake to theorize before one has data. Insensibly, one begins to twist the facts to suit theories, instead of theories to

[ PODCAST OF THE WEEK]

#BigData @AnalyticsWeek #FutureOfData #Podcast with Dr. Nipa Basu, @DnBUS

 #BigData @AnalyticsWeek #FutureOfData #Podcast with Dr. Nipa Basu, @DnBUS

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[ FACT OF THE WEEK]

Retailers who leverage the full power of big data could increase their operating margins by as much as 60%.

Sourced from: Analytics.CLUB #WEB Newsletter

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