KAN Practical Implementation (Kolmogorov–Arnold Networks Algorithm)

#kan #Kolmogorov–ArnoldNetworks #mlp #deeplearning #machinelearning #ai

In this video, I tried to implement Kolmogorov–Arnold Networks (KAN) Algorithm using imodelsx library.

The KAN is an approach in the field of machine learning that is based on the Kolmogorov-Arnold representation theorem from mathematical analysis. This method applies the theorem's insights to build predictive models for complex, high-dimensional datasets. KAN uses the idea that any multivariate function can be decomposed into sums and compositions of univariate functions.

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You can access the notebook on KAN implementation of the video from here: https://github.com/manishasirsat/kan-...

You can watch a video on KAN: Kolmogorov–Arnold Networks Paper Explained from here:    • KAN: Kolmogorov–Arnold Networks Paper...  

Github repository for the code: https://github.com/manishasirsat/rag-...

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⏱️ Timestamps
0:00 Intro
0:33 Problem statement
1:40 'imodelsx' python library
2:07 Agenda
3:35 Data processing
5:10 KAN implementation without hyper-parameter tuning
6:35 KAN implementation with hyper-parameter tuning
9:00 A KAN model with the best accuracy on heart disease classification