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Project: Scientific Data Analysis
Finally, some cleaning’s done on my very first Jupyter notebooks created between 2018-2019. Back then, I wasn’t capable of coding from scratch, so it was a process of literally copying & pasting chunks of code from the internet and running the woven code by hit-or-miss. Now that I became more proficient in Python, it was time to do some pruning and organization on these notebooks. …
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WITH clause
Technical tests given during interview processes have been real boosting materials that led me to look for the better solutions to answer the questions. One of the querying techniques I enjoyed using recently is the WITH clause. It is used for creating subquery blocks which are known as Common Table Expressions (CTE). …
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Garbage in, garbage out: Dealing with outliers
Recently I was asked to justify my choice of leaving outliers -instead of removing them- during a technical interview for a data scientist position. The interview was based on a pre-handed take-home test where I provided a time series forecast related to a specific business case. …
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Project: Mobile Transaction Fraud Detection
In this 2-week project, I aimed to try something completely different from what I practiced in the previous project. Instead of the text data, there were 6M rows of numbers. Rather than munging the data for purely personal interest, I built predictive models that can potentially address a business solution for mobile fraud detection. …