Self Organizing Feature Map Kohonen Maps Solved Example | Self Organizing Networks by Mahesh Huddar

Self Organizing Feature Map Kohonen Maps Solved Example | Self Organizing Networks by Mahesh Huddar
The following concepts are discussed:
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Self Organizing Maps,
Self Organizing Maps - Kohonen Maps,
self-organizing maps in machine learning,
self-organizing map example,
self-organizing maps clustering,
self-organizing maps deep learning,
self-organizing maps in neural networks,
self-organizing maps algorithm,
self-organizing feature map,
kohonen self organizing feature map
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[@wailshudar]

Excellent, but I wish you also talked about competitive vs cooperative learning

[@tehreemqasim2204]

great video. best tutor on youtube

[@MaheshHuddar]

Thank You
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[@anjalis1812]

Thanks for the video: I am not sure if this is the correction, but initial weight matrix at 1:38 timestamp and at1:54 during 1st Iteration is different.

[@ramankr0022]

Immensely Helpful. Thank You Sir.

[@MaheshHuddar]

Welcome
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[@scienceforeveryone8827]

sir, why are u updating the weights of the winning neuron while the loser weights are remained untouched...?

[@aaronneutron]

I think the reason for updating the weights of the winning neuron while leaving the loser weights untouched can be explained through Donald Hebb's principle: "Cells that fire together, wire together." This principle suggests that our brains learn by strengthening connections between neurons that are simultaneously activated. In the context of the video, the winning weights were adjusted because they represented the strongest connections, indicating which neurons were most active and thus should be updated.

[@EarthyHaven5911]

Very helpful 👍

[@MaheshHuddar]

Thank You

[@shubhamrajpurohit4405]

Thank You Sir!

[@MaheshHuddar]

Welcome
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[@helene367]

PLEASE SIR CAN U GIVE ME YOUR EMAIL I WANT TO ASK YOU PLEASE THANK YOU IN ADVANCE@@MaheshHuddar

[@vgreddysaragada]

well explained ..Thank you

[@MaheshHuddar]

You are welcome
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[@Unk-rf4ik]

You also explained very well sir ..Thank you

[@raniaelrifai3337]

Thanks doctor, please, how we can determing the number clusters?

[@praneshchow]

probably unit 1 and unit 2 are the cluster.

[@adeebashoaib8286]

well explained!

[@MaheshHuddar]

Thank You
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[@MadaraUchiha-wj8sl]

Nicely explained

[@MaheshHuddar]

Thank You
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[@Harleenkaur-yp2el]

Thanku sir

[@MaheshHuddar]

Welcome
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[@lradhakrishnarao902]

Best

[@MaheshHuddar]

Thank You
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[@StayStudywithMonikaSharma]

good,sir sir plz back propagation algorithm ko ek example ke throu samjha dijiye jisme bias bhe ho

[@MaheshHuddar]

Follow these videos
ua-cam.com/video/n2L1J5JYgUk/v-deo.html
ua-cam.com/video/ItkSCYzSD34/v-deo.html

[@MaheshHuddar]

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[@ahmedraza6257]

Sir do we have to udpate initial rate or it remains constant?

[@lakshay1667]

We have to update the weights of the cluster the input data belongs to

[@ahmedraza6257]

@@lakshay1667 so no change in alpha?

[@lakshay1667]

@@ahmedraza6257 alpha is the learning rate, it is pre set and remains constant throughout

[@ahmedraza6257]

@@lakshay1667 ok thnx

[@surajklverma]

Sir where can we find this ppt❤ please

[@dhruvtiwari4836]

Take ss