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[ COVER OF THE WEEK ]
Convincing Source
[ AnalyticsWeek BYTES]
>> The Quantum disruption in Global Business driven by The Big Analytics by analyticsweekpick
>> Hacking journalism: Data science in the newsroom by analyticsweekpick
>> 7 Things to Look before Picking Your Data Discovery Vendor by v1shal
[ FEATURED COURSE]
Learning from data: Machine learning course
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[ FEATURED READ]
Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, 4th Edition
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[ 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:How to efficiently scrape web data, or collect tons of tweets?
A: * Python example
* Requesting and fetching the webpage into the code: httplib2 module
* Parsing the content and getting the necessary info: BeautifulSoup from bs4 package
* Twitter API: the Python wrapper for performing API requests. It handles all the OAuth and API queries in a single Python interface
* MongoDB as the database
* PyMongo: the Python wrapper for interacting with the MongoDB database
* Cronjobs: a time based scheduler in order to run scripts at specific intervals; allows to bypass the rate limit exceed error
Source
[ VIDEO OF THE WEEK]
Future of HR is more Relationship than Data – Scott Kramer @ValpoU #JobsOfFuture #Podcast
Subscribe to Youtube
[ QUOTE OF THE WEEK]
Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world. Atul Butte, Stanford
[ PODCAST OF THE WEEK]
Subscribe
[ FACT OF THE WEEK]
40% projected growth in global data generated per year vs. 5% growth in global IT spending.