Neural network

My 4-steps to learn deep learning for genomics

Step 1, get a high-level understanding Watch statquest by Josh Starmer. 1blue3brown deep learning playlist Step2, code it out! If you are into python, watch “The spelled-out intro to neural networks and backpropagation: building micrograd”: I still code in R for most of the time, so I walk through the R code in the deep learning with R book.

How to code a variational autoencoder (VAE) in R using the MNIST dataset

Imagine you have a bunch of pictures of cats, and you want to find a way to generate new cat pictures that look similar to the ones you have. A variation autoencoder (VAE) is like a magical tool for creating these new cat pictures. Here’s how it works: Encoder: The VAE first takes your cat pictures and passes them through an encoder. This encoder is like a detective that tries to capture the important features of the cats, such as their fur color, size, and shape.