KAN Practical Implementation (Kolmogorov-Arnold Networks Algorithm)
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- Опубліковано 8 чер 2024
- #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: github.com/manishasirsat/kan-...
You can watch a video on KAN: Kolmogorov-Arnold Networks Paper Explained from here: • KAN: Kolmogorov-Arnold...
Github repository for the code: github.com/manishasirsat/rag-...
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Generative AI Playlist: • The Era of 1-bit LLMs:...
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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
Never thought an Indian will pick up kan and explain as the youtube is flooded with resnet and titanic ds
I will definitely try to learn something from her. Even if I dont understand anything.
You are doing great mam! Keep going on
Thank you! Keep watching 👍
Very useful, and keep posting the videos. Definitely, one day you'll achieve more views!@
Thanks for the kind words:)
@@airesearcher24 where are you doing research.
Could you please explain hyperparametr fine tuning in details to achieve best results.
Yes, I can.. thanks for the suggestion:)
Best explanation on KAN.Please make a comparison video with MLP
Certainly, keep watching 👍
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Can I get your mail?
Here it goes: airesearchstudies@gmail.com