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.
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.
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.
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. 😊
Great course !
Questions : what is the meaning of layer ? or what adding layers will provide to the network ?!
Great, great great explanation, thanks
Amazing, thank you.
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.
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.
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.
:)
Too fast even for someone like me who have some idea about these.