Back in college, I did a class project where I used computer vision techniques for the first time. It was the age before deep learning. Today, I want to revisit this old project.
A tutorial to create a recommender pipeline with Kedro and MLFlow.
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My Heritage In Color
An uploaded family photo inspired me to pick up a colorizer tool. Here is my post honoring my family’s history.
MLOps is all about creating sustainability in machine learning. To maintain structure in this fast-paced field, you can try out Kedro, an open-source Python project that aims to help ML practitioners create modular, maintainable, and reproducible pipelines.
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R-Recommender Roadtrip
This is part 2 of my talk on recommenders. The presentation describes the intuitions of matrix factorization and how to implement it in R. I delivered this in the R-Users Group PH meetup group this November. If you wish to see some more recommender material in this blog, check this out:
With data, I explore the name Cassandra, Zoe, their variants and how they move in popularity over time.
Learning ATGC seem too different from the rest of the cash-cows of data science. Fast forward half a decade, we see viral RNA and reverse transcription polymerase chain reaction (RT PCR) flying around in the news.
What’s a data scientist to do? Learn!
In this video, I’ll discuss my solution to the SIIM-ISIC Melanoma Classification Challenge hosted in Kaggle.
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Mobility in the time of pandemic
Mobility is one of the greatest freedoms achieved in the 20th century. Deep-rooted as it is, free movement is something easy to forget. As a data scientist, this article is about how data reflects our shared quarantine experience.
Today I will be taking a look at blood chemistry tests and COVID-19. I am trying to see associations of the different blood cell types when there is a SARS-COV-2 infection. I am joined with my friend Dr. Earl Tiu as I try to explain my findings to him. The data is sourced from Kaggle, […]
It is the REAL DYL 