Visualizing High Dimension Data Using UMAP Is A Piece Of Cake Now

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Google colab link: colab.research.google.com/dri...
UMAP (Uniform Manifold Approximation and Projection) is a novel
manifold learning technique for dimension reduction. UMAP is constructed
from a theoretical framework based in Riemannian geometry and algebraic
topology. the result is a practical scalable algorithm that is applicable to
real world data. UMAP algorithm is competitive with t-SNE for visualization quality, and arguably preserves more of the global structure with
superior run time performance. Furthermore, UMAP has no computational
restrictions on embedding dimension, making it viable as a general purpose
dimension reduction technique for machine learning
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Опубликовано:

15 авг 2022

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Комментарии : 30

@krishnaik06 Год назад

Happy 76th Independence Day ❤ On this auspicious day, we at iNeuron.ai have made the Tech Neuron available for lifetime access for the next 7 days. We as a team want to contribute to our country by educating Indians at an affordable price and with excellent quality content🙌🏻 Celebrate Azadi Ka Amrit Mahotsav With 250+ Courses Lifetime Access With 20% Discount Ab code Karega INDIA • Get access to 200 + Courses for a lifetime for a limited period (Starting from 15th august to 21st August) with a 20% Discount • Job portal access • Resume Building with experts every month unlimited times • Mock interview with techies every month unlimited times. • Live doubt clearing all day for 6 hours Tech Neuron Link: ineuron.ai/one-neuron/Tech-Neuron You can also avail additional 20% discount by using coupon code KRISH20 Happy Learning to all🙌🏻

@saiprasanth3668 Год назад

Sir u re the The absolute Legend

@lifted1785 Год назад

looking forward to playing around and experimenting w UMAP today. Will read the paper first, the new approach seems v promising!

@shekharkumar1902 Год назад

We were missing your leagendry videos Krish ; keep it up for keep your fans learning continue.

@ramkrishnachoursiya7817 Год назад

I was looking for same information on UMAP 4 months earlier but there was not proper available on internet for applying it. But its good to see and learn this technique and use it, mostly in bioinformatics field.

@kvafsu225 Год назад

What an amazing presentation.

@russelldicken9930 Год назад

Wow! Thanks for sharing.

@lifted1785 Год назад

good shit krish keep it up brother! 👍✊

@shripadjoshi7158 Год назад

Very Nice and Helpful

@sandeshgowdru8869 8 месяцев назад

this is a life safer, lets understand data even better... thanks a lot for sharing this..

@ravichandra4289 Год назад

It is very interesting sir to see taking biological topic in coding and explaining...

@Shisuiii69 Год назад

Sir, I'm deploying car price prediction ml model to streamlit and after clicking predict button I'm getting error one hot encoder has no attribute '_infrequent_enabled' Can you please tell me how solve this🙏

@kaustubhkapare807 Год назад

Thank you sir

@bencyshaji7557 Год назад

How to find the optimal value of n components where 90% of data is retained?

@rahulnag6589 Год назад

Sir, May I access the study materials for data science from my mobile phone hence I don't have any laptop or computer

@kakabudi Год назад

Would this work for feature selection?

@meshmeso 3 месяца назад

Trying to implement feature selection and dimensionality reduction using selectkbest and pca but my runtime keeps crashing.

@user-pm4ei7ur7b 7 месяцев назад

Can umap be applied to visualize more than 3 bands say 10

@indolizacja9829 4 дня назад

Have you considered comparing UMAP and Concordex?

@hardikvegad3508 Год назад

Krish can you make Playlist explaining all the computer vision transfer learning models such as VGG16, XCEPTION,... etc, bcz implementing them it's very easy but explaining them is very tedious 🥴😅...