Hey thanks for the kind words! Will do, I have a few more videos ready for next week :) Do let me know if there is a specific topic or question you would like covered!
Thank you very much ..😊 A very good explanation. Breaking it down into simpler concept. Liked the way you explained how 1x1 conv is networks in networks.
Very useful indeed, I just think the 3D representation could be a bit better (I'm used to seeing the filter rectangle behind the first layer and not on the side, but that's probably just me)
Glad you liked it. It’s the second time this week I had this request for where to start in deep learning, I’m setting up a video on that topic will publish soon!
![The moment we stopped understanding AI [AlexNet]](http://i.ytimg.com/vi/UZDiGooFs54/mqdefault.jpg)
Perfectly Explained! Thanks :)
Thank you for breaking it down so well! Keep up the excellent work!
Hey thanks for the kind words!
Will do, I have a few more videos ready for next week :)
Do let me know if there is a specific topic or question you would like covered!
Thank you very much ..😊
A very good explanation. Breaking it down into simpler concept.
Liked the way you explained how 1x1 conv is networks in networks.
Glad it was useful :)!
You made this concept so easy to understand: thank you!
I am glad it was useful :)
Very useful indeed, I just think the 3D representation could be a bit better (I'm used to seeing the filter rectangle behind the first layer and not on the side, but that's probably just me)
True, it’s titled by about 90 degrees.
Otherwise the 1x1 convolution wouldn’t fit well in the image I believe.
Shouldn't we call it a 1 x 1 x Cin convolution?
That would indeed be a less confusing name for sure. That thing already have like 7 different names though haha
I like your explanations, but Im watching it randomly
As I'm beginner, where should I start?
Glad you liked it.
It’s the second time this week I had this request for where to start in deep learning, I’m setting up a video on that topic will publish soon!