Dataviz with Python
By Reiichiro Nakano. There are a number of visualizations that frequently pop up in machine learning. Scikit-plot is a humble attempt to provide aesthetically-challenged ...
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Google releases massive visual databases for machine learning
This article was written by Richard Lawler. Richard’s been tech obsessed since first laying hands on an Atari joystick. . Millions of images and YouTube videos, ...
Journey Science in Telecom: Take Customer Experience to the Next Level
Journey Science, being derived from connected data from different customer activities, has become pivotal for the telecommunications industry, providing the means to dras...
Are typos and small mistakes making your business data inaccurate?
As typos and spelling mistakes make up to 58% of data inaccuracy issues, here we look at how much even a small mistake can cost your business… According to Experian,...
Who are you, Data Scientist? Answer with a survey
Originally posted on Data Science Central “I keep saying that the sexy job in the next 10 years will be statisticians, and I’m not kidding”. Hal Varian,&...
Top 30 people in Big Data and Analytics
Originally posted onData Science Central Innovation Enterprise has compiled a top 30 list for individuals in big data that have had a large impact on the development or p...
Dark Data: The billion dollar opportunity
Every organization collects, stores and retains portions of dark data. It’s the digital equivalent of emotional baggage which hangs around after every user interaction,...
DSC Webinar Series: Optimizing Analytical Insights, Data Security and Visualization
How do you gain visibility and insights from all your data when you are faced with analyzing over 4M records from 5 different systems? Join us for this latest Data Scienc...
Why data preparation should not be overlooked
Data is the new language today. Data leads to insights, and insights help organizations to make actionable business decisions. However, sourcing the data and preparing it...
Why Data Decays so Fast?
People change jobs, get promoted and move home. Companies go out of business, expand and relocate. Every one of these changes contributes to data decay. It’s been sai...