Building a Neural Network with PyTorch in 15 Minutes | Coding Challenge

[@mesembria95]

Nick, we appreciate your work so much. The way you offer your knowledge so graciously, you're helping so many people who are newbies in the field.

[@NicholasRenotte]

Knowledge is one of the few things you can give away and not lose, so why not share?! Thanks so much for checking it out @NeonCone!

[@andyweb7779]

The amount of calculating a Terminator has to do just to work out if someones boots, clothes and motorcycle will do him is wild lol.

[@FleiX664]

Imagine Skynet.

[@baguette184]

youre literally the best, i genuinely appreciate all the work youve put out for us. you have no idea how much help your channel has given me, without you i wouldve been completely lost in everything, thank you so much, i love you 😭♥

[@sadra2637]

Good job man. I feel more and more in love with ML and DL as I watch your videos. Keep it up. 👊

[@NicholasRenotte]

YESSS, love that you're getting into it!

[@mansoorbaig9232]

Great explanation of all that is need in 15 min. Keep up the good work, your tutorials are a great help to DS community.

[@petegrapentien4147]

This is the most fun I've ever had watching a coding video

[@thealmighty9]

Wow this was so good! I can't believe you still take time to explain things throughout the challenge lol. I am loving this series, super fun :D

[@jinparksoul]

"I can't believe you still take time to explain things throughout the challenge". I can't literally can't believe it either. Drink a shot every time he typed a line with no explanation and you'll be dead half way through the video. There is no freaking way a beginner understands wtf just happened by the end.

[@thealmighty9]

@@jinparksoul This video isn't a tutorial for beginners though, it's a challenge he made for himself. If you want a tutorial look through his countless videos where he explains every little thing that even you can understand.

[@jinparksoul]

@@thealmighty9 Nonetheless its still true that most of the lines are written without any explanation regardless of who it is targeted towards in contradiction to what your comment "you still take time to explain things" implies. Although not really done here taking time to explain everything is typically something you would not need to do when you target experienced AI researchers and pytorch devs.

[@thealmighty9]

@@jinparksoul So there is only explain everything or nothing? Only beginners and experienced professionals? "Take time to explain things" is not saying "takes time to explain every little thing" I'm not sure what you're trying to get at here, I don't know if you're upset that he doesn't explain enough or upset that he explained anything at all.

[@erfanelmtalab1615]

nick you are my hero for real , thank you for your tutorials man !

[@NicholasRenotte]

Ayyyy, thanks so much @Erfan!

[@primeq]

great job Nick. It's impossible to overstate how powerful speed, clarity are when it comes to learning/teaching. 🌟

[@qybl]

So entertaining, yet so educational. this format is awesome! Thank you Nicholas

[@gustavojuantorena]

This is awesome Nick! I'm amazed by the way you can also explain while coding really fast 😂

[@NicholasRenotte]

I have no idea how I pulled this off 😂

[@gabrielj.9028]

Great job! Your videos have really helped me with project ideas and application examples. Looking forward to seeing more!

[@NicholasRenotte]

YESSS, go getem @Gabriel!! Plenty more to come.

[@nicky6917]

This is the longest 15 min ever in my life

[@AsherNoor777]

Yo! that is EPIC! Super intense! and SUPER helpful! thank you so much for sharing, this is giving me hope for my ML project for sure! And yes, I TOTALLY take this as a Win. Amazing job!

[@vincentmarkiet]

Awesome stuff. Keep at it mate.

[@NicholasRenotte]

Cheers Vincent!!

[@TheCopernicus1]

Awesome content as always mate! well done :)😀

[@NicholasRenotte]

Cheers @Bass Azayda!!

[@rverm1000]

Glad you got it deploy. No one seems to get that far

[@Markom3D]

Hey, i might have to take this format for my live streams…. Subscribed good sir

[@papakamirneron2514]

Finally, a tutorial for just the useful stuff

[@gadmuhirwa5226]

oohh my God you made proud and happy you build my confidence brother @ Nicholas I can't stop laugh for your celebration

[@dasamlan9874]

Great vid. I started ML a year ago and I could understand approx 70-75% of the vid.... can u do a vid on audio processing or provide some resources for the same. Audio processing, noise classification and similar stuffs. And once again a BIG thank u for these vids.. really helpful!!

[@NicholasRenotte]

Heya @Das, check this out: kzbin.info/www/bejne/kH2sgZ6joql9d8U

[@dasamlan9874]

@@NicholasRenotte once again.. Thanx a lot. 😁

[@omarkhamismohamed9563]

Super underrated .. Amazing explanation during challenge !!!!

[@ganesh-uc2ft]

This was fun! Thank You for the amazing tutorial.

[@nerualbrain]

Love this video It actually helped me start using pytorch

[@anshverma2820]

Thanks Nick! That was an amazing video.

[@NicholasRenotte]

Thanks a mil for checking it out @ansh!

[@MatthewOrbuch]

If this were not a rushed challenge but a proper tutorial explained a bit more calmly, it would be pure gold

[@sanketdongre369]

Put the code in chatGPT and ask for explanation. 😇

[@choz8358]

Thanks for the content, as a newb I learned a lot here 👍

[@bguerrae]

That was incredible! thank you so much for making it look so easy to implement. you are great!

[@sergioquijano7721]

Shortcut of the video? Toggle/Hide command line inside VSCode: ctrl + J (command + J in mac) Hope you remember my shortcuts

[@lakshman587]

So you won!! Congratulations!!!!

[@NicholasRenotte]

I have never written 50+ lines of code so fast in my life!! Thanks a mil @Lakshman. Was looking close towards the end there!!

[@lakshman587]

@@NicholasRenotte Noice! You did it!!

[@philtoa334]

Great ! but... This time I especially learned that I could have bad thought for you . For a gift card ... 🤣

[@NicholasRenotte]

LOL I think the code that series isn’t ending anytime soon. might just need to start making some ridiculous challenges.

[@saleemmuhammed5133]

This is what I exactly wanted.. Awesome stuff!!

[@armaaanziyad2772]

Nick amazing work you really are a pro!

[@NicholasRenotte]

You're too kind, thanks @Armaaan!

[@gplgomes]

Nocholas, you are the guy.

[@NicholasRenotte]

Cheers @Geraldo!

[@justinbenavidez1985]

great video and amazing coding!!

[@irugal8964]

😎 We always appreciate your content Nich

[@NicholasRenotte]

Thanks a million @Irugal, means a ton!!

[@ChrisOndrovic]

Man awesome video, do you have or could you do one doesn't have to be a timed coding challenge but instead if you want to create your own dataset as opposed to using an existing one

[@einsteinsboi]

Legend! That was epic!

[@NicholasRenotte]

Thanks a mil @maryml

[@MichaelMacedoDiniz]

Very nice content, congratulations !!!!

[@billal2731]

I can finally ad Machine Learning to my resume

[@sitrakaforler8696]

Dam dude !!!!!!!!!!!!!!!!!!!!!!!!! You are wild ! Bravo

[@Ragul_SL]

why are we giving (1,32,(3,3)) in conv2d and then (32,64,(3,3)) , how is it decided? can someone explain

[@robotbugs]

When I did it with the same code, the loss went down and then back up again - why is that?

[@OvettaSampson-vz4en]

This was fun to watch.

[@NanoCreator]

This is a good teaching!!! you are great!!!

[@murataavcu]

That was truly amazing

[@NicholasRenotte]

Thank you so much @Murat!!

[@harshraithatha]

Hey Nick, I have sensitive data in my dataset. I need it to train my model. But also want to mask it. What to do?

[@NicholasRenotte]

I deal with this a lot at work, check with your privacy policies but the model itself won't contain the raw data just what the NN has learned.

[@julianchambrier2401]

Good job and Congratulations ! Is it possible to make a video on lip sync with Tensorflow from a video file and a text/audio file generating a deepfake? For example a video of you with speech of Martin Luther King (with your voice) ? I think it could interest a lot of people

[@NicholasRenotte]

Oooooh, I'll dig into it!

[@neilrenaud5962]

Job well done .Way to go

[@fizipcfx]

Do you plan to make another streams.

[@NicholasRenotte]

OFC, normally aim for two a week. This week was a bit of an exception.

[@fizipcfx]

@@NicholasRenotte i got you, thanks for the reply

[@johnnovotny4286]

well done, appreciated

[@mahsakhoshnoodi2972]

Nice challenge 🤩

[@NicholasRenotte]

Thanks a mil @Masha!!

[@toni3124]

Love your vids! could you maybe make a video about a TTS system based on the LJ Speech Dataset?

[@NicholasRenotte]

Will take a look!

[@GX-uq1hm]

Nicholas, what monitors do you use there for coding? your workplace looks fantastic !!

[@epistemicompute]

You have no pooling layers

[@domillima]

what rig do you have for your two curved monitors? :D

[@HussainAyed-y3s]

This dude is an O.G.

[@adityashukla7849]

Phenomenal!

[@NicholasRenotte]

Cheers @Aditya!

[@dsc40sundar18]

preety amazing and big fan bro

[@dactoanho6026]

Thank you very much for your video. it's very helpful

[@vinsmokearifka]

Haha very interesting show

[@krale9970]

Csn you tell me on which learn platforms i can learn this clearly , because for a beginner I dont know what you write in general there . Where should I start to beginnt with to understand this ? Thank you for help in advance

[@akandee]

Great! Nicholas, thanks for sharing. Please how would one handle labels for classification, is this method foolproof to using LabelImg? Thanks.

[@wgb-10]

Good job Nick! Huge W. I was wondering as to why the loss was increasing after every 4 epochs, is it because a new batch is fed in to the model?

[@NicholasRenotte]

Heya Wesley!! First one finally!! Probably getting to the point of overfitting but we're only printing out after every epoch not per batch. Loss bumps up in epoch 4 but still drops in epoch 8 (take a look at the power e-6 as opposed to e-5)

[@wgb-10]

@@NicholasRenotte Oh right. I completely missed the e-6 😂

[@JasR-b2r]

I am brand new in learning python code and neural nets etc and I feel the exact same way as you did @ 9:45 LOL

[@coolsai]

God level

[@vladrask]

Hi What VS Code theme are you using?

[@dsc40sundar18]

love from india and i am so happy

[@ravenbao3334]

i added another pic of a number 5, but I get this error - Given groups=1, weight of size [32, 1, 3, 3], expected input[1, 4, 28, 28] to have 1 channels, but got 4 channels instead; how can I make it work

[@Spacesparx-h7q]

Can you put a video about creating a AI for beginners including all mechane learning code like computer vision and more in one video

[@ajaykumar-rh2gz]

Amazing bro love the way teach

[@chiragparmar3678]

one question i have is why did u not defined your yhat as clf.predict(x) instead you took only clf(x)

[@jamesderiter4370]

This dude is an irl character from bigmouth

[@adamblack2255]

IS it just me or is pytorch incredibly slow? Or am I misunderstanding the difference between this and a simple conv model with tensorflow/keras?

[@NicholasRenotte]

Hmmm, might need to do a comparison, tbh I've always used tf and never had performance issues. I didn't check how many samples were in the MNIST dataset for this though.

[@kamalakannank2741]

Sir, Which document you read to write this code?

[@dadanny661]

Instead of printing the epoch loss, didn't you print the loss of the last batch of the epoch ?

[@cagataydemirbas7259]

Hi, Im confused about cross validation. I looked videos they just use cross_val_score. I want to train data using cross validation and predict test daha how can I do it with cross validation. I want train cross validation and apply other datas how can i do it

[@NicholasRenotte]

Take a look at GridSearchCV in sklearn

[@cagataydemirbas7259]

@@NicholasRenotte thank you. gridsearh tests some parameters after tested when we predict it uses best parameters ? or should we trained again by best parameters

[@nikaize]

Easy !!!! Good job !!!

[@sebastianrothe]

awesome & fun , at least if you don't try to follow typing :) thx alot

[@NicholasRenotte]

LOL, yeah it was a little fater than my usual pace

[@sebastianrothe]

@@NicholasRenotte but it was Fun trying :) Maybe you can do a series like this From tiny world problem to live solution? That would be cool to See the process and thoughts

[@MrSanselvan]

Nice. The loss is increasing after the 3rd epoch. Is it good sign or bad ?

[@danielpaul8734]

It is not. Notice that the loss will be written in scientific notation after the 3rd epoch

[@georgebassemfouad]

Hi I have a question.. what is the difference between tensorflow and pytorch

[@NicholasRenotte]

Similar, just different implementations TF: from Google, PT: from Facebook

[@Michal2SAB]

Why sometimes in accuracy, loss or whatever, one of these.. weird letters are present? Like a big number 0.12202020202-e545. Is it a problem? I found that to be confusing when predicting cause then the model inaccuratly predicts for some reason. Or perhaps it's not a problem and I just can't do simply "if accuracy > 0.5" in that case and THAT's the issue

[@Connecttechaarushenglish-ox111]

No it is not a problem. Sometimes, when accuracy or loss or both are very small or big then it uses some words like 341e78

[@Nmind-Nbody]

Awesome Broo!!!😱

[@fairyroot1653]

Can this model predict a sequence of numbers in captcha based images with digits and/or letters?

[@NicholasRenotte]

Would need to be tweaked to do that!

[@fairyroot1653]

@@NicholasRenotte can you demonstrate how?

[@gblazerify]

Amazing!

[@SomebodythatIusetoknow123]

well played

[@chiscoduran9517]

Hi, there is something that always confused me when working with conv networks, when you set the input layers in the nn.Linear(), you set it as 64*(28-6)*(28-6), why is that? how to know how many inputs and outputs you have to have when combining conv nodes with linear nodes, thanks great video :)

[@NicholasRenotte]

Look under the shape section here: pytorch.org/docs/stable/generated/torch.nn.Conv2d.html , the formula for calculating the height and width of the output are shown there (see Hout and Wout)

[@NicholasRenotte]

If I adjusted kernel size, padding or stride then the output shape would’ve changed accordingly @Chisco!

[@nikitaandriievskyi3448]

If you have an image of let’s say 28*28 shape, and you pass it through a 3by3 filter with a stride of 1, and 0 padding, then ur output Shape would be: 28-3 + 1 by 28-3+1. The general formula for shapes after passing through a conv layer is ((input_shape +2*padding size - filter size) / stride) + 1 and then floor the results, so if it’s 3.5 you should round to the bottom, and you will have 3

[@NicholasRenotte]

What Nikita said is bang on!

[@alexzan1858]

does pytorch have better/faster training compared to tensorflow?

[@fizipcfx]

Awesomeee

[@mishmohd]

11:17 don’t u need to put it in eval mode when predicting and train mode when training?

[@shishya]

And you didn't skip commenting 😅

[@arjunbali2079]

Hi Nicholas I started following your channel after your series on siamese network. Like this can we build multiple language OCR for example in a sentence there is english, hindi and german together written the classifier translate them all together and give us the result in the required language

[@hlslaughter3]

You've got 5 minutes to write hello world. Me: .... (◉▂◉ ) ..... (⊙.⊙) .... 5 mins later .... .... ¯\_(ツ)_/¯

[@andyweb7779]

Is the tensor mathematics involved in neural networks the same as the tensor mathematics invented by Albert Einstein for his work on general relativity?

[@dubble_g]

i have way more detailed images that are 128x128 and my NN is really bad at predicting, any tips what i should try to adjust besides the learnign rate?

[@Michallote]

Use yolo

[@fahnub]

You da GOAT

[@rodrigovbaautomation8703]

Yessssssss!!!!!

[@SimpliSave-h2o]

Could this be used to bypass Robot image validation ?

[@thiagosnelli138]

Hi mate, I'm using the CPU, what should I type on line 57?

[@thiagosnelli138]

Well, answering my own concern, for the CPU guys: line 58 change for: clf.load_state_dict(torch.load(f, map_location='cpu'))

[@undokat]

6:08 i don't know what you are doing what are those?

[@fulltimefrontend]

Tell how to build my machine ! I want to setup just like you have.