Explanation of the data set: MNIST Data Set(784 Dimensional) Lecture 9 @Applied AI Course

[@muhammadawais2173]

I search this topic all the way on youtube but the way you explained it no one explained like that. thanks, you have a great skills for teaching

[@RideLikeAChamp]

1 min into the video - just want to say wow . Simply superlative explanation

[@ege5785]

Sir, you explained what I didn't understand before. Thank you!

[@kyrav9]

thank you for explaining mister, very much appreciated.

[@sophieleigh17]

answering all my questions. Thank you!

[@TheBaliyarsinghDiscourse001]

Great Explanation. At time stamp 6.30 you mentioned that there are 28 rows and 28 columns. But if we count it's 14x14. Am I missing something here? I would also like to understand how the values are assigned to the grey pixels?

[@KhaliDALKhafaji]

that was wonderful what is the name of software that you are using for annotation

[@bcinerd]

where is the machine learning playlist?

[@yashverma9443]

Nice Explanation!!! please upload more vedios..

[@geekavenue]

really good video clip. nice explanation!

[@oparaanita9524]

this is such a wonderful explanation

[@danishshaikh1003]

Really appreciate your efforts.

[@vikramsingh-oi5dg]

sir Thank you so much , it really helped me.

[@intljofcompnetworkscommuni98]

great explanations! Thanks!

[@venkateshmunagala205]

Nice explanation

[@himanshupant3176]

Great explanation.

[@arpanpaul3498]

Where is the link??

[@AppliedAICourse]

please check description part
www.appliedaicourse.com/course/applied-ai-course-online/lessons/mnist-data-set784-dimensional/

[@guptamols]

colah.github.io/posts/2014-10-Visualizing-MNIST/

[@liviumircea6905]

Very good

[@ajaykumar-iq5nf]

Sound of this lecture is very low..one can listen properly by using earphones

[@sau002]

Excellent

[@AndayRubin]

@Applied AI Course where can I watch the next video for this lesson?

[@AppliedAICourse]

Plz chk this playlist: ruclips.net/p/PLupD_xFct8mH9Sg1Lnav2eEA8Unf4l3b4

[@AndayRubin]

@@AppliedAICourse thank you so much

[@TheJayenz]

Thank you sir

[@jishnu1258]

Thank u very helful

[@pavankatasani5181]

x1.5 ;