We can turn a simple autoencoder into something sophisticated. Autoencoders discover a latent mapping z, which as a lower-dimensional representation of the input x, can be useful for pre-training networks and creating recommender models. However, how autoencoders compress information may come in millions of ways. To truly polish how z can be generated, we turn […]
Tag: machine learning
Medicine is quite different from my profession but I think having this kind of interest is healthy (get it?). Eventually, I came to reach some parallels between my discipline and the medical sciences.
Autoencoders are a simple neural network approach to recommendation
Variational autoencoders can discover unique ways to encode-decode the input from a distribution. Bonus: It can generate images!
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.
In this video, I’ll discuss my solution to the SIIM-ISIC Melanoma Classification Challenge hosted in Kaggle.
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 