Visualizing neural network using python

Question

I'm implementing an algorithm to classify messages into topics using a neural network. I'm wondering if there are library to help me visualize the training process like the one you can find here :

I'm going to do the classification of three-dimensional data instead of two-dimension. How can we do it?

Also, in the link above, I don't understand the first layer input where we have a fixed horizontal line and a vertical line perception. Can we set out the first layer of the neural network to be like that using sci-kit learn?

Answer 1

Yes, but any good one won't be nearly as simple as the linked playground, and will require some familiarization. Below is a list of such libraries, & links to my answers w/ visualization functions you could adapt to your application:

• iNNvestigate , classifier introspection (first image below)
• Saliency maps , extracted features introspection
• TensorBoard , full model introspection, highly configurable, but complex
• LSTM/CNN Visualization , simple function (second image below)
• Weights visualization , simple function

(Answer assumes you're using TensorFlow)

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