How Big Data Is Boosting Emergency Preparedness
We never feel prepared when disaster strikes – from the devastation of Hurricanes Katrina and Sandy to the Pacific earthquake that moved the main island of Japan and ca...
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Common Probability Distributions: The Data Scientist’s Crib Sheet
This post was written by Sean Owen. Data scientists have hundreds of probability distributions from which to choose. Where to start? Data science, whatever it may be, r...
See this simple introduction to Natural Language Processing (NLP)
Today, with of Digitization everything, 80 percent the data being created is unstructured. Audio, Video, our social footprints, the data generated from conversation...
Statistics Means Never Having to Say You Are Certain!
When I was a kid there was a popular movie quote going around, “Love means never having to say you’re sorry” which was the basis behind this T-shirt my ...
Adapting an Algorithm to Real-time Applications
Below are some images generated by an algorithm that I originally created to study stocks. The stock in this case is Yahoo! in the early 2000s. I realize that none of the...
Use Neural Networks to Find the Best Words to Title Your eBook
Contributed by Bernard Ong. He enrolled in the NYC Data Science Academy 12-week full time Data Science Bootcamp program taking place between July 5th to September 23r...
Relationship between Insider Trading & short term stock prices
Contributed by Sharan Duggal. Introduction Insider Trading is often associated with the illegal activity of trading in shares of ones company based on material non publi...
Can computers think? An epistemology for Artificial Intelligence
As AI enters our homes through smart home devices or tries to conquer our streets through self-driving cars, one need not be a Luddite to contemplate the potentially heav...
Analyzing The Hype Around Big Data – A Balanced View
In my previous articles on ‘What I Wanted To Know About Big Data But Was Afraid To Ask’ series, I covered ‘What is Big Data’ and ‘Who came up with Big Data a...
How signal processing can be used to identify patterns in complex time series
The trend and seasonality can be accounted for in a linear model by including sinusoidal components with a given frequency. However, finding the appropriate frequency for...