Pytorch Neural Network example

An example and walkthrough of how to code a simple neural network in the Pytorch-framework. Explaining it step by step and building the basic architecture of the fully connected network.

Written blogpost if you prefer to read:

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[smileyley]

I love how you explain everything line by line briefly, without digging deep into the math. Just a perfect Tutorial how to create a simple Network. Will watch all of your vids!

[Iffythegreat]

This was a life saver for my 4th year neural networks course. A lot of the other tutorials start out at a much higher level of using pytorch, this takes it to the basics. Great video!

[beizhou]

For these who have already some experiences on other DL frameworks, such as Tensorflow, this tutorial is probably the best to get your hand dirty on the transfer to PyTorch framework by getting the landscape of building Neural Neural in just one short video.

[osielvivar]

Fantastic, I followed the blogpost which was excellently written. Thank you!

[parthchokhra]

I am following your completely series for my 100 days ml challenge. This is what I needed. Precise accurate and easy to understand.

[ADV_UA]

Yey, my first pytorch tutorial is successfully completed! Thank you!

[quicano]

This was a great Video, straight to the point, very clear and very helpful, thanks!

[hackercop]

I'm moving from tensorflow to pytorch, this is really helpful thanks

[maryfrancesgleason]

Bravo. Very well done. Fastest and best explained implementation of mnist. When I coded along in google colab, most of the code autocompleted. Worked the first time with no errors. Amazing.

[thecros]

Man thank you so much....I found what ever I wanted and I am so so happy to find you ....will be watching all of your videos and thank you so so so much

[gabriele]

Wow, a perfect explanation. Thank you

[lattellieeeee]

Clear and concise! Thanks for this video, it helps a lot!!!

[balicien]

I shared your tutorials on LinkedIn. Your channel is awesome for a newbie on these subjects. I appreciate you.

[yanxu]

firstly, very exciting and concise tutorial! really enjoy watching your videos.

secondly, is there any way to predict class probability? e.g. max(softmax(dim=1)(scores))?

finally, is there any way to estimate prediction confidence (or variance)? so that if the model's prediction has low confidence, we could just output "not sure".

[neildutoit]

Thanks this was pretty straightforward.

[nasirrahim]

Great Explanation. I have one question though. You did not use softmax layer to out probabilities for 10 classes?

[suyashsingh]

I love your page bro, appreciate your hustle. Don't stop your flow.

[xv]

Exactly what I was looking for. Thank you.

[juleswombat]

Many Thanks. That was nice an clear brief description on pytorch.
The only bit I am am still a little confused about, where do have to say .to(device). It looks like just put the data and the model is sufficient to ensure all calculations done on on the GPU?
It would be nice to have a similar style video on actor critical models, and how controls which parts we back propagate errors through and those parts we don't