10 Rules for Creating Reproducible Results in Data Science

In recent years evidence has been mounting that points to a crisis in the reproducible results of scientific research. Reviews of papers in the fields of psychology and cancer biology found that only 40% and 10%, respectively, of the results, could be reproduced. Nature published the results of a survey of researchers in 2016 that […]
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Machine Learning using Spark and R

R is ubiquitous in the data science community. Its ecosystem of more than 8,000 packages makes it the Swiss Army knife of modeling applications. Similarly, Apache Spark has rapidly become the big data platform of choice for data scientists. Its ability to perform calculations relatively quickly (due to features like in-memory caching) makes it ideal […]
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3 Claims from Facebook Yarn Developers

Facebook recently released an alternative to Node Package Manager (npm). It’s called Yarn and, according to the developers, is designed to improve on npm in the following areas: Speed Determinism Security Let’s examine each of these claims in more detail. 1. Speed Yarn claims to be a faster than npm. I ran a test where I […]
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10 Internet of Things Security Vulnerabilities

If the 2017 Consumer Electronics Show (CES) is anything to go by, 2017 will be a major year for the Internet of Things (IoT). Unfortunately, it’s also going to a bumper year for cyber security exploits—including novel, and potentially catastrophic, attacks. As such devices come of age we are going to start seeing them everywhere. […]
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Assumptions Can Ruin Your K-Means Clusters

Clustering is one of the most powerful and widely used of the machine learning techniques. It’s very seductive. Throw some data into the algorithm and let it discover hitherto unknown relationships and patterns. K-means is the most popular of all the cluster algorithms. It’s easy to understand—and therefore implement—so it’s available in almost all analysis […]
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