CNN Explainer: An Interactive Tool You Always Wanted to Try to Understand CNNs

Convolutional Neural Networks (CNNs) have been a revolutionary deep learning architecture in computer vision.

The core component of a CNN is convolution, which allows it to capture local patterns, such as edges and textures, and helps in extracting relevant information from the input.

Yet, at times, understanding:

• how CNNs internally work

• how inputs are transformed

• what is the representation of the image after each layer

• how convolutions are applied

• how pooling operation is applied

• how the shape of the input changes, etc.

…is indeed difficult.

If you have ever struggled to understand CNN, you should use CNN Explainer.

It is an incredible interactive tool to visualize the internal workings of a CNN.

Essentially, you can play around with different layers of a CNN and visualize how a CNN applies different operations.

Clicking on any of the core operations (convolution, max pooling, activation) will make the entire internal workings super clear to you.

Yet, if you find any issues, let me know.

Try it here: CNN Explainer.

👉 Over to you: What are some interactive tools to visualize different machine learning models/architectures, that you are aware of?

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