Tag: Data Analysis

K-Means Explained

K-Means, a method of vector quantization that is popular for cluster analysis in data mining, is about choosing the number of clusters, selecting the centroids (not necessarily from the dataset) at random K points, assigning each data point to the closest centroid (forming K clusters), computing and placing the new centroids of each cluster, reassigning…

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Data Science In Healthcare

Healthcare is a promising industry for implementing Data Science solutions. Years before the rise of IT departments in the hospitals, the patients’ data were collected and stored, and each client had an archive file describing his health history. This data is highly valuable for improving diagnosis, analyzing symptoms, and making it easier for medical professionals to…

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Data Science In Banking

Imagine you take out several loans from different sources. A good data scientist will be able to flag you as a good target for a credit consolidation offer. Reversely, this might also work against you, highlighting your high credit risk.   Nowadays, using Data Science in Banking is a necessity, not a luxury. Either a…

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Statistics Misinterpreted​​

Statistics is one of the most powerful tools for driving change in any Business, however, if misused or misinterpreted, it will lead to producing biased results. Let’s split the misinterpretation of statistics into 3 main points for better understanding, with real-life examples: Bias, non-random and small samples: Having 3 out of 4 rich adolescents from New York…

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