Infographic: The Typical Data Scientist Profile in 2019
This infographic was produced by 365DataScience. Last year they completed a research on 1,001 data scientists to get a profile of the ‘typical’ data scientist in 201...
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The 10 Statistical Techniques Data Scientists Need to Master
This article was written by James Le. Here is a brief summary. Link to the full article is provided at the bottom. Some techniques are not mentioned in Le’s article...
10 Machine Learning Methods that Every Data Scientist Should Know
Machine learning is a hot topic in research and industry, with new methodologies developed all the time. The speed and complexity of the field makes keeping up with new t...
Drive Better Outcomes by Combining the Strengths of Data and CX
At first glance, data science and customer experience (CX) don’t have much in common. Data scientists like me are typical left-brained thinkers: detail-oriented, logica...
Untapped Economic Assets? How to Monetize Your Dark Data
What if you had a corporate asset that was never used? Your first response might be that corporate asset obviously has no value. And you’d probably be right. Howeve...
Three-way data splits (training, test and validation) for model selection and performance estimation
The use of training, validation and test datasets is common but not easily understood. In this post, I attempt to clarify this concept. The post is part of my forthcomi...
Data Science Lessons from the Apollo Moon Landing
Landing a man on the moon 50 years ago was a true feat of genius, and an outstanding collaboration between many different stakeholders with many differing individual agen...
Data Science Applications In Various Industries
The amount of data generated today is astonishing. Research published by Seagate reports that by 2025, around 175 Zettabytes of data will be generated on an annual base. ...
DSC Webinar Series: Accelerate Analytics Projects with Data Prep on AWS
Leveraging the benefits of effective data preparation to help build a modern ERP system is a vital component in innovating an organization’s data workflow systems. ...
Data Cleaning and Wrangling With R
Originally posted by Michael Grogan. One of the big issues when it comes to working with data in any context is the issue of data cleaning and merging of datasets, since...