Issue #39    Web Version
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[  COVER OF THE WEEK ]

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[ LOCAL EVENTS & SESSIONS]


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[ AnalyticsWeek BYTES]

>> Train, Score, Repeat, Watch Out! Zillow’s Andrew Martin on modeling pitfalls in a dynamic world. by analyticsweek

>> @ChuckRehberg / @TrigentSoftware on Translating Technology to Solve Business Problems #FutureOfData by v1shal

>> The Secret to Business Users Understanding Big Data: Enterprise Taxonomies by jelaniharper


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[ NEWS BYTES]

>>  MapR Customers Share Big Data Experiences – Datanami Under  Big Data

>>  Snapchat Will Let Media Partners Aggregate, Monetize User Posts – Variety Under  Social Analytics

>>  Data Analytics Add Value to Healthcare Supply Chain Management – RevCycleIntelligence.com Under  Health Analytics


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[ FEATURED COURSE]

Python for Beginners with Examples

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A practical Python course for beginners with examples and exercises.... more


[ FEATURED READ]

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

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In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Mast... more


[ TIPS & TRICKS OF THE WEEK]

Winter is coming, warm your Analytics Club
Yes and yes! As we are heading into winter what better way but to talk about our increasing dependence on data analytics to help with our decision making. Data and analytics driven decision making is rapidly sneaking its way into our core corporate DNA and we are not churning practice ground to test those models fast enough. Such snugly looking models have hidden nails which could induce unchartered pain if go unchecked. This is the right time to start thinking about putting Analytics Club[Data Analytics CoE] in your work place to help Lab out the best practices and provide test environment for those models.


[ DATA SCIENCE Q&A]

Q:How do you test whether a new credit risk scoring model works?
A: * Test on a holdout set * Kolmogorov-Smirnov test Kolmogorov-Smirnov test: - Non-parametric test - Compare a sample with a reference probability distribution or compare two samples - Quantifies a distance between the empirical distribution function of the sample and the cumulative distribution function of the reference distribution - Or between the empirical distribution functions of two samples - Null hypothesis (two-samples test): samples are drawn from the same distribution - Can be modified as a goodness of fit test - In our case: cumulative percentages of good, cumulative percentages of bad
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[ VIDEO OF THE WEEK]

#FutureOfData with @theClaymethod, @TiVo discussing running analytics in media industry

 #FutureOfData with @theClaymethod, @TiVo discussing running analytics in media industry


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[ QUOTE OF THE WEEK]

The data fabric is the next middleware. Todd Papaioannou


[ PODCAST OF THE WEEK]

Ashok Srivastava(@aerotrekker @intuit) on Winning the Art of #DataScience #FutureOfData #Podcast

 Ashok Srivastava(@aerotrekker @intuit) on Winning the Art of #DataScience #FutureOfData #Podcast


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[ FACT OF THE WEEK]

As recently as 2009 there were only a handful of big data projects and total industry revenues were under $100 million. By the end of 2012 more than 90 percent of the Fortune 500 will likely have at least some big data initiatives under way.


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*This Newsletter is hand-curated and autogenerated using #TEAMTAO & TAO, excuse some initial blemishes. As with any AI, it may get worse before it will get relevant, excuse us with your patience & feedback.
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