Confusion Matrix Tensorboard

In this article I’ll explain how you can create a confusion matrix with TensorBoard and PyTroch. At the end of this article you will find the link to this code on my GITHub. If you need a confustion matrix without TensorBoard you can jump to the following tutorial here:

Let’s start and load the data:

Loading the FashionMNIST datatset.

The confusion Matrix:

The Conv-Net:

This is a simple architecture of a Conv-Net. Not fancy but it works!

Convolutional Neural Network.

Train the data:

Feed the Conv-Net with the data. Reduce the epochs if you have a slow CPU.

Object detection takes no longer than a coffee.
Object detection takes no longer than a coffee.

A short tutorial that shows you how to do realtime object detection with Pytorch with a pretrained Faster R-CNN model. The model is trained with the COCO dataset.
My recommendation is that you should run that code on a NVIDIA card. Otherwise, object detection slows down.

Before you start!

Grab a coffee and start coding!

This is a short tutorial on how to create a confusion matrix in PyTorch. I’ve often seen people have trouble creating a confusion matrix. But this is a helpful metric to see how well each class performs in your dataset. It can help you find problems between classes.

Confusion Matrix MNIST-FASHION dataset
Confusion Matrix MNIST-FASHION dataset
Confusion Matrix MNIST-FASHION dataset

If you were only interested in coding the matrix. Jump directly to “Build confusion matrix” at the end of this article. You will also find the link to my code on GITHub at the end.

If you want to use Tensorboard instead go to:

For all others… first things first. Let’s start…

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