TensorFlow GPU on Ubuntu 24.04: The Complete Guide (CUDA, cuDNN, TensorRT) - Jupyter lab and VS Code

Ready to unlock the power of TensorFlow GPU on your Ubuntu 24.04 machine? This comprehensive guide walks you through the entire installation process, from setting up the NVIDIA drivers to configuring CUDA Toolkit, cuDNN, and TensorRT.
No prior experience necessary! We'll break down each step clearly, making it easy for beginners to follow along.
Boost your Deep Learning workflow by learning how to integrate Jupyter Lab for interactive coding and VS Code for a powerful development environment.
By the end of this video, you'll be equipped to:
Install TensorFlow GPU on Ubuntu 24.04
Configure CUDA Toolkit, cuDNN, and TensorRT for optimal performance
Set up Jupyter Lab for interactive coding
Integrate VS Code for a streamlined development experience
Don't waste time searching for scattered information. This video is your one-stop shop for installing and using TensorFlow GPU on Ubuntu 24.04!
Commands Link:
github.com/mah...

[@Syed-m4h]

To anyone else searching, this is the one you have been looking for. A walkthrough smoother than butter. You,Sir , are a world class instructor and deserve the utmost recognition for this intuitive demonstration. Liked and subscribed.

[@baldrianforte]

Thanks for the tutorial. I was so frustrated because with different tutorials on the internet there were always different strange error messages that I couldn't understand. (I want to switch from Windows to Ubuntu and don't know Linux well yet) I spent several evenings digging through forums and installation guides. This guide is the first one that works as stated in the video.

[@caslor2002]

Thanks for the excellent and simple tutorial !!

[@tanviran]

You just saved my life, bro! Big thumbs up. Keep up the good works. ❤

[@benoitschillings]

Thank you SO MUCH !!! I wasted two evening trying to install tf & cuda on my machine. this worked beautifully. Can NVIDIA learn to write some documentation.....

[@jlyonia]

Please add me to the list of people praising your efforts here in creating this video. Thank you so much. Your assistance was invaluable. Thanks for sharing your knowledge so completely and simply.

[@luiscaamano]

Excellent. You're the man.

[@WahnsinnigeTraeume]

Great video. This was my tenth attempt and your video finally helped. Thank you!

[@kyoungjh1011]

Amazing! Thank you so much!!

[@oziousmegasus9201]

you deserve 1M likes, I have been trying to install this for months, even the official TF doesnt show how to install tensorrt.

[@VioFax]

It's gate keeping. Plain and simple. It's all by design. So drunk grandpa's can't build a terminator.

[@payafarhadbahman976]

Man, for me it was rocket science, but I did it finally. Kudos to you. I had to reinstall everything from scratch 3 times, because everytime a single mistake on the way ruined everything. Thank you very much!
On another note, why does it have to be super lengthy? Can't they just create a package for every GPU that's capable of tf and py to have all these features in it installed, or ready to be installed?

[@TheRealDanNguyen]

excellent video - thank so much! (now subcribed to your channel)

[@lowkeyleanin]

YOU ARE SUCH A LEGEND!!! You made this just for us 🥹🥹🥹🥹 I will acknowledge you in my work. Thanks a lottttt

[@TechJotters24]

Thank you!!!

[@brianpark999]

Hi, thank you for the video.
I solved these problems with TensorFlow 2.16.1
Thanks again!!!!
Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered

[@szymonsitarz5007]

Hi, could you tell me how you solved this problem?

[@brianpark999]

@@szymonsitarz5007 Hi, I just added the version option when I installed TensorFlow! Only 2.16.1 worked for me.

[@szymonsitarz5007]

​@@brianpark999 Thank you so much! That solved my problem :D

[@brianpark999]

@@szymonsitarz5007 My pleasure!! I'm so glad to hear that!!!!!

[@mmammams]

You are the Boss! You have earned a like and a subscribe!

[@TechJotters24]

Thanks for your support!!!

[@mejanlamichhane8752]

Thank you . Apparently tensorflow installation guide itself mentions to use just pip and not conda and it's easier Ig

[@shemescobal3325]

This tutorial is great!

[@Ben-dj4tx]

This is what I am looking for.

[@egocentric879]

im getting when i try to run the sudo sh command stating failed to verify the gcc version
how to fix it?

[@rafamarinho87]

On the step: ./test_cudnn at 11:09 my initialization has failed. Any thoughts on how to handle it?

[@TechJotters24]

What errors did you get?

[@louisbroucke2990]

@@TechJotters24 I have the same issue, no errors. I run test_cudnn and it outputs 'cuDNN initialization failed.'
All the previous steps worked though. I have an RTX3060 laptop.

[@rafamarinho87]

@@TechJotters24 No errors before. Everything exactly like the example. Do you have any tips to debug what is happening when I run "./test_cudnn"? I have an RTX 3050 laptop

[@TravelJotter24]

@@rafamarinho87hi, can you please send me the errors? I’ll check it.

[@rafamarinho87]

@@TravelJotter24 I am already sending you the errors I have so far. The only thing I have is "cuDNN initialization failed". The script test_cudnn.c states the following "// test_cudnn.c
#include
#include
int main() {
cudnnHandle_t handle;
cudnnStatus_t status = cudnnCreate(&handle);
if (status == CUDNN_STATUS_SUCCESS) {
printf("cuDNN successfully initialized.
");
} else {
printf("cuDNN initialization failed.
");
}
cudnnDestroy(handle);
return 0;
}" So if status was CUDNN_STATUS_SUCCESS it would print "cuDNN successfully initialized". In my case status was not CUDNN_STATUS_SUCCESS because it has printed "cuDNN initialization failed".
What I am asking is if you have any tips to understand why cuDNN was not initialized. And even tips to debug the initialization so I can send you the errors