Almog

Photo by CDC on UnsplashIn this post I’m going to review a recent paper in the interface between medicine research and modeling and machine learning. The paper, Green, A.G., Yoon, C.H., Chen, M.L. et al. A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis. Nat Commun 13, 3817 (2022). https://doi.org/10.1038/s41467-022-31236-0 , describes two approaches to training neural network models for predicting the resistance of a given M. tuberculosis (MTB) strain,…

How GANs work and how you can use them to synthesize dataFig. 1 — Synthetic images of a person, generated entirely by a GAN. Image source: https://thispersondoesnotexist.com/ . License: https://github.com/lucidrains/stylegan2-pytorch/blob/master/LICENSE (MIT)If you’re working in deep learning, you’ve probably heard of GANs, or Generative Adversarial Networks (Goodfellow et al, 2014). In this post we will explain what GANs are, and discuss some use cases with real examples. I am adding to this post a link to my GAN…

How to train them and how they work, with working code examplesA big decision tree in Zimbabwe. Image by author.In this post we’re going to discuss a commonly used machine learning model called decision tree. Decision trees are preferred for many applications, mainly due to their high explainability, but also due to the fact that they are relatively simple to set up and train, and the short time it takes to perform a prediction with a decision tree. Decision trees are natural to tabular data, and, in fact, they currently…