Neural Networks in R

In this episode, I dive into my very first hands-on experience building a neural network in R—complete with the raw, messy, exciting learning process. I walk through loading and preparing data, constructing a sequential model with Keras, understanding epochs, loss, and validation error, and even visualizing predictions and computing variable importance. Along the way, I share my thoughts as a statistician exploring machine learning and reflect on what neural networks might offer beyond traditional models like random forests. If you're curious about how to think about neural nets, debug your R+Keras setup, or understand what your model is doing under the hood, this is for you.

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The dataset comes from this paper: https://journals.plos.org/plosone/art...

For my previous video on neural networks, see    • Neural Networks Explained by a Skeptical S...