This post is a tutorial demonstrating how to use Grad-CAM (Gradient-weighted Class Activation Mapping) for interpreting the output of a neural network. Grad-CAM is a visualization technique that highlights the regions a convolutional neural network (CNN) relied upon most to make predictions. While Grad-CAM is applicable to any CNN, it is predominantly employed with image classification models. This tutorial utilizes TensorFlow for implementation, but I made a parallel tutorial that works with PyTorch.

This post is a tutorial demonstrating how to use Grad-CAM (Gradient-weighted Class Activation Mapping) for interpreting the output of a neural network. Grad-CAM is a visualization technique that highlights the regions a convolutional neural network (CNN) relied upon most to make predictions. While Grad-CAM is applicable to any CNN, it is predominantly employed with image classification models. This tutorial utilizes PyTorch for implementation, but I made a parallel tutorial that works with TensorFlow.

This post shows how to load and evaluate the model we built in the previous post.

This is post is a walkthrough of creating a Siamese network with FastAI. I had planned to simply use the tutorial from FastAI, but I had to change so much to be able to load the model and make it all work with the latest versions that I figured I would turn it into a blog post. This is really similar to my other post on Siamese Networks with FastAI, except that in this one I will follow on with a post about how to evaluate the model.

Distributions are super important. In this post, I’ll talk about some common distributions, how to plot them, and what they can be used for.

This post contains instructions for how to work with personal access tokens on GitHub.

This is Part II of two posts demonstrating how to get test metrics from a highly unbalanced dataset. In Part I, I showed how you could theoretically estimate the precision, recall, and f1 score on highly unbalanced data. In this part, I’ll do the same thing with a real dataset. To do so, I’ll use the Adult Income Dataset.