KAN Practical Implementation (Kolmogorov–Arnold Networks Algorithm)
Skills:
ML Maths Basics70%
Key Takeaways
Practical implementation of Kolmogorov–Arnold Networks Algorithm using imodelsx library
Original Description
#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.
--------------------------------------------------------------------------------------------------------------------------------------------------------------
You can access the notebook on KAN implementation of the video from here: https://github.com/manishasirsat/kan-implementation
You can watch a video on KAN: Kolmogorov–Arnold Networks Paper Explained from here: https://www.youtube.com/watch?v=AyM9YqU923k
Github repository for the code: https://github.com/manishasirsat/rag-llm-demo
--------------------------------------------------------------------------------------------------------------------------------------------------------------
Generative AI Playlist: https://www.youtube.com/watch?v=ID04YmgzM38&list=PLzkBTicHqQFmdF62zHHramnBRZl6zUvmR
--------------------------------------------------------------------------------------------------------------------------------------------------------------
Connect with me on social media platforms:
Website: https://ai-researchstudies.com/
Google scholar: https://scholar.google.com/citations?user=kM4QN-8AAAAJ&hl=en
LinkedIn: https://www.linkedin.com/in/manishasirsat
GitHub:https://github.com/manishasirsat
Quora: https://machinelearningresearch.quora.com/
Blogger: https://manisha-sirsat.blogspot.com/
Twitter: https://twitter.com/ManishaSirsat
⏱️ Timestamps
0:00 Intro
0:33 Problem statement
1:40 'imodelsx' python library
2:07 Agenda
3:35 Data processing
5:10 KAN implemen
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: ML Maths Basics
View skill →Related Reads
📰
📰
📰
📰
A lightweight workflow for keeping up with AI conference papers
Dev.to · Daniel
Why CitedEvidence Believes Great Researchers Read Less Than You Think
Medium · AI
How to Write a Literature Review That Actually Argues Something
Medium · Machine Learning
I Built a Personal Paper Engine to Stop Losing Research Papers
Dev.to · Ethan
Chapters (6)
Intro
0:33
Problem statement
1:40
'imodelsx' python library
2:07
Agenda
3:35
Data processing
5:10
KAN implemen
🎓
Tutor Explanation
DeepCamp AI