A web app is essential for demonstrating your NLP/ML solution to colleagues and clients. But building and deploying one can be a nightmare at times. Enter Gradio.

Gif of sentiment analysis web app by Chua Chin Hon.


Visual/data analysis of 271 people in Singapore who tested positive for Covid-19 despite having one or two shots of the vaccine. This is not a medical study.

Breakdown of 271 breakthrough Covid-19 cases in Singapore by gender, symptomatic and vaccination status. Interactive Flourish chart available here.


Going straight from audio to a range of text-based NLP tasks such as translation, summarisation and sentiment analysis

Chart: Chua Chin Hon


Efficient transcription of audio files has been one of the major “missing links” in modern NLP — till now. Enter Hugging Face’s implementation of Facebook’s Wav2Vec2 model, which produces impressive out-of-the-box results.

Poet Amanda Gorman delivering the inauguration poem on Jan 20, 2021. Screen-capture via PBS NewsHour’s YouTube clip.


Forecasters correctly predicted that Joe Biden will win, but vastly underestimated the strength of support for Donald Trump. A quick post-mortem suggests that the polls and forecasts became too bullish after August 31.


Despite the political drama in the home stretch of the US presidential election, two months-long forecasts have held surprisingly steady in projecting a clear win for Joe Biden on Nov 3.

Joe Biden and Donald Trump at their final presidential debate on Oct 23. Screen-grab via C-Span.

Trump’s down in the polls, and forecasts by experts point to a decisive loss on November 3. He doesn’t even seem to be doing as well on Twitter as he did in 2016. Is it game over for the White House incumbent?


With all eyes on the outcome of the Nov 3 vote, which metric, poll or forecaster can accurately predict the outcome of a highly volatile race for the White House? Probably none in isolation, but an aggregate of reputable forecasts might help.

Screen-cap of first 2020 US Presidential Debate on September 29: C-Span’s YouTube live-feed.


A practical use case on fine tuning a Distilbert model on a custom dataset, and testing its performance against more commonly used models like Logistic Regression and XGBoost

Illustration of web app by: Chua Chin Hon


Small batch machine translation of speeches and news articles (English to Chinese/Tamil, and vice versa) in under-30 lines of code, using Hugging Face’s version of MarianMT and Facebook’s Fairseq.

Illustration: Chua Chin Hon

Chua Chin Hon

Data Science | Media | Politics

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