20: Hopfield Networks - Intro to Neural Computation

[@xjyang001]

Thank you, Dr. Fee, for the 20 great lectures!

[@jumperkables9372]

Absolutely fantastic video and lecturing, the pivotal concepts are perfectly addressed and understood!

[@charliehuang5571]

thanks for this amazing lecture series! this course had really good pacing and intuitive explanations on both the neurobiological and mathematical backgrounds

[@ritviz2027]

I have not watched it and planning to watch.
Is this much graduate level coursework or higher ?

[@bowenzheng8580]

@@ritviz2027 Hi, this is an undergraduate course. For the technical part, it only requires high school level math background. The neuroscience part is explained very well such that it requires little prior knowledge.

[@anb4351]

Thanks mit for all this

[@sinaazartash3566]

Oh my God! That would be an amazing research project. Some future neuroscience grad student. Consider this. 1:12:20. Perhaps confusion is the brain being stuck at a local minimum that is not optimum yet

[@danbocker7398]

fantastic lecture

[@woowooNeedsFaith]

45:51 - That is not correct. It should be sgn[1/3( 1 1 -1)]. The result is the same though (because of sign).
It has to be just a copy-paste error form previous example at 44:59.

[@cledybecerra654]

Thank you!

[@not_amanullah]

thanks ♥️🤍

[@PREMKUMAR-wz6gq]

51:15 the network is not guaranteed to reach exactly the stored pattern? Some noise appears to remain.

[@SmartClassroom10]

Good

[@yepan8321]

No one realized that there is a mistake on the slide 26.

[@binxuwang4960]

you are right... the values are not correct for the matrix multiplication. While the final answer is correct

[@arcturusgd]

5 million subs 13 comments bro fell off

[@niccolocordini]

bruh

[@phasor50]

bruh

[@not_amanullah]

this is helpful ♥️🤍