Site blog
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January 2018Data Manipulation and Exploration with Dplyr
The Curious Oenophile The dplyr package in R is a powerful tool to do data munging and manipulation, perhaps more so than many people would initially realize, making it extremely useful in data science. Shortly after I embarked on the data science journey earlier this year, I came to inc...
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December 2017An Introduction to Learn R Programming
R Programming has an extremely vast package ecosystem. It provides robust tools to master all the core skill sets of data science. For someone like me, who has only some programming experience in Python, the syntax of R programming felt alienating, initially. However, I believe it’s j...
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November 2017Autonomous Technology: Facing the Dilemmas of Self Driving Car Ethics
New Technology, New Problems Self-driving car ethics require proper study, training, and attention to detail. We must understand the ethical concerns in order to minimize risk. When it comes to autonomous technology of any kind, the first thing that often comes to our minds is our safety, our w...
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November 2017Data Ethics: Keeping Your Ethics in Check as a Data Scientist
As data scientists, we are all in this to pursue the objective truth, or close to it. Check your ethics with these bad data ethics examples. You’ve probably come across this before:A vendor skews a graph that compares their product with a competitor’s in the market.A survey convenient...
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November 2017Detecting Algorithmic Bias and Skewed Decision Making
Just like humans, algorithms can develop bias and make skewed decisions. What are these biases and how do they impact decision-making? An Algorithmic Bias in the Making If we took a hard look at every model ever built for classifying who is the optimal candidate for: a credit loan ...
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November 2017Understanding Data Security and Access Control
There’s more to data security and access control than granting teams within a company different access levels and issuing user passwords.As data scientists, our jobs are not to run the whole security operation in our organizations. However, as we work very closely with data, it is essential that...
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November 2017Data Privacy and Data Anonymization Techniques
Do you think about your privacy? Do you wonder why data privacy and data anonymization are important? Read along to find all the answers. Internet companies of the world have the resources and power to be able to collect a microscopic-level of detail on each and every one of its users and build...
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October 2017Spooky Author Identification | Exploratory Data Analysis in R
This blog is based on some exploratory data analysis performed on the corpora provided for the “Spooky Author Identification” challenge at Kaggle. The Spooky Challenge A Halloween-based challenge [1] with the following goal: predict who was writing a sentence of a possible spooky ...
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October 2017Data Science and Law: What One Lawyer Learned From a 50-Hour Data Science Bootcamp
Is there a relation between data science and law? Here's what a lawyer learned from a 50-hour data science bootcamp at Data Science Dojo.With an increased focus on the growing role of data science and data analytics in the future of law, I decided that it was high time to learn what all the fuss i...
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October 2017Ethics in Research: Conducting A/B Testing on Customers
Ethics in A/B testing is essential. A/B testing might not be as simple and harmless as it looks. Learn how to take care of ethical concerns in A/B tests.The Ethical Way to A/B Test We have come a long way since the days of horrific human experiments during World Wars, the Stanford prison experime...