Deep Learning and Neural Network Introduction with Keras (3.1)

[@bmpatton13]

Thank you so much for helping teach others about this amazing technology. I'm not even in the same state as you but your videos and your GitHub walk-through have been amazing so far. I eagerly look forward to the rest of this material and hope others can find these videos.

[@BiancaAguglia]

I like how you take the time to include useful diagrams and other visuals. They make it much easier to understand the lecture. Well done again. 😊

[@abdelwahidbenzerrouk8271]

Great course ! Questions : what is the meaning of layer ? or what adding layers will provide to the network ?!

[@sandipprabhu]

Great, great great explanation, thanks

[@mdsifath7741]

in y=mx+c there is no weight in c(y intercept).But in the video there is weight multiplying with the bias. Please help me understand.

[@stevedevney7322]

I believe the values are m, and c in your model that are being influenced by the NN. That is why it doesn’t need an extra weight.

[@godos22]

I don't know if I'm the only one who can see it, but on page www.heatonresearch.com/aifh/vol3/deriv_sigmoid.html , the LaTeX code does not display correctly.

[@aleksandrkanygin2672]

Amazing, thank you.

[@Diamond_Hanz]

:)

[@AmeerulIslam]

Too fast even for someone like me who have some idea about these.