Finding meaning in data using stepwise regression

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How do you find meaning in data? In our mini project, my friend @ErikaSM and I seek to predict Singapore’s minimum wage if we had one, and documented that process in an article over here. If you have not read it, do take a look.

Since then, we have had comments on our process and suggestions to develop deeper insight into our information. As such, this follow-up article outlines two main objectives, finding meaning in data, and learning how to do stepwise regression.

The Context

In the previous article, we discussed how the talk about a minimum wage in Singapore has frequently…


How similarly do different machine learning algorithms perform?

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In my module “Developing Meaningful Indicators” , a classmate (Nicole) used Azure Machine Learning on Excel to conduct sentiment analysis on over 4000 Pfizer-related tweets in order to determine how most people felt about the vaccine.

She discovered that the sentiments of tweets were quite evenly spread out, with “negative” having a slight gain over “positive”. This means that the opinion amongst Twitter users are relatively mixed, having a healthy mix of both positive and negative opinions about the Pfizer vaccine. This can be seen in the graph that she posted below.


A learning process using Python, SQL, AWS Comprehend, and Tableau

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In this semester, I took up a class called ‘Developing Meaningful Indicators’ under Dr Charles. I was inspired when he mentioned that he was trying to do some natural language processing on a huge data set of Reddit comments. In fact, two of my classmates (Nicole and Min Yi) had also used Microsoft Azure AI on Excel to conduct sentiment analysis on Twitter tweets.

So I teamed up with my classmate, who is aiming to make a real change in the world, Ling Hui, and attempted to do this for ourselves. We initially hypothesised that people on Reddit would generally…

Ryan Kwok

A student studying Information Security (Computing) and trying to use technology to make a positive impact in the world

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