Aug 09, 18: #AnalyticsClub #Newsletter (Events, Tips, News & more..)

[  COVER OF THE WEEK ]

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Conditional Risk  Source

[ LOCAL EVENTS & SESSIONS]

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> 2018 Trends in Artificial Intelligence: Beyond Machine Learning for Internal and External Personalization by jelaniharper

>> Customer Loyalty Resource for Customer Experience Professionals by bobehayes

>> Estimating Other “Likelihood to Recommend” Metrics from Your Net Promoter Score (NPS) by bobehayes

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[ NEWS BYTES]

>>
 Goldman Sachs enlists staff for cyber security war games – Financial Times Under  cyber security

>>
 DECKER NAMED TO GOOGLE CLOUD ACADEMIC ALL-DISTRICT® FIRST TEAM – Dominican College Athletics Under  Cloud

>>
 Kadant Inc (NYSE:KAI) Institutional Investor Sentiment Analysis – Frisco Fastball Under  Sentiment Analysis

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[ FEATURED COURSE]

Machine Learning

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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]

Antifragile: Things That Gain from Disorder

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Antifragile is a standalone book in Nassim Nicholas Taleb’s landmark Incerto series, an investigation of opacity, luck, uncertainty, probability, human error, risk, and decision-making in a world we don’t understand. The… more

[ TIPS & TRICKS OF THE WEEK]

Data Analytics Success Starts with Empowerment
Being Data Driven is not as much of a tech challenge as it is an adoption challenge. Adoption has it’s root in cultural DNA of any organization. Great data driven organizations rungs the data driven culture into the corporate DNA. A culture of connection, interactions, sharing and collaboration is what it takes to be data driven. Its about being empowered more than its about being educated.

[ DATA SCIENCE Q&A]

Q:Compare R and Python
A: R
– Focuses on better, user friendly data analysis, statistics and graphical models
– The closer you are to statistics, data science and research, the more you might prefer R
– Statistical models can be written with only a few lines in R
– The same piece of functionality can be written in several ways in R
– Mainly used for standalone computing or analysis on individual servers
– Large number of packages, for anything!

Python
– Used by programmers that want to delve into data science
– The closer you are working in an engineering environment, the more you might prefer Python
– Coding and debugging is easier mainly because of the nice syntax
– Any piece of functionality is always written the same way in Python
– When data analysis needs to be implemented with web apps
– Good tool to implement algorithms for production use

Source

[ VIDEO OF THE WEEK]

Making sense of unstructured data by turning strings into things

 Making sense of unstructured data by turning strings into things

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[ QUOTE OF THE WEEK]

Data are becoming the new raw material of business. – Craig Mundie

[ PODCAST OF THE WEEK]

Understanding #BigData #BigOpportunity in Big HR by @MarcRind #FutureOfData #Podcast

 Understanding #BigData #BigOpportunity in Big HR by @MarcRind #FutureOfData #Podcast

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[ FACT OF THE WEEK]

By 2020, at least a third of all data will pass through the cloud (a network of servers connected over the Internet).

Sourced from: Analytics.CLUB #WEB Newsletter

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