Beginner Deep Learning Tutorial in PyTorch | How to Make a Convolutional Neural Network | Tutorial 1

Explaining the effects of batch size, learning rate, loss function, cross entropy function. Calculating model gradient / derivatives through backpropagation, forward pass, backward pass through the network.
The Colab Notebook: colab.research.google.com/dri...
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[@GregHogg]

Take my courses at mlnow.ai/!

[@spirit1484]

this is dope, thank you so much. Would love to see more in this series

[@GregHogg]

Thanks a ton - I will try!

[@meenakshichippa260]

At every point video was informative and interesting. The way you communicate is very easy to understand

[@TheMISBlog]

Very useful Video, thanks greg

[@GregHogg]

Glad to hear it! You're very welcome:)

[@itsRemco]

Bro that was such a clear tutorial, I subbed

[@GregHogg]

Woot, enjoy!

[@user-wr4yl7tx3w]

great explanation.

[@GregHogg]

Really glad to hear that!!

[@AminYas]

Great video

[@GregHogg]

Thanks very much! :)

[@mahmoudmohsen7989]

Great job greg
Would you do sequance models in pytorch ,please?

[@GregHogg]

Absolutely will do, just wait :)

[@user-rs4sg2tz6k]

Why didn't you use the chroma key to make the background transparent?

[@dev_jun]

Make long tuts

[@GregHogg]

35 minutes is pretty long!

[@dev_jun]

@@GregHoggyes it is

[@mikekertser5384]

For some reason, Pytorch seems to be much more complicated than TF...

[@GregHogg]

It's a lot more code. But it's very flexible, and once you get used to it, you may like it better. Or maybe not :)