this is good i have learned a lot. how ever i have been trying to make a streamlit application form model deployment that when i input the data as it is in the data set i must get prediction of the failure just to test the model can any one help me
it´s an old dataset i found on github, i recommend you to take a look on this site for dataset: mal-net.org/ and this repo: github.com/TanayBhadula/malware-image-detection.
@@databowlrecipes318 thanks for your response My question is, I want to add data to the data set that you posted. That is, benign and new malware files. When I convert files to images, each file is converted into a large number of images with my standard size. How do I know which image to transfer from a malware file to the malware folder and which image to transfer from a benign file to the benign folder in order to finally train them all?
Hi i'm sorry, i tried this script on my colab and got a problem in tensorboard, its didn't showing result like scalar and hparam like in your videos can u help me sir? thankyou
@@databowlrecipes318 yes i have, other command run smoothly like in the video but when it come to this command %reload_ext tensorboard %tensorboard --logdir ./runs/ the result didn't show up when i try again it say 'Reusing TensorBoard on port 6006 (pid 115), started 2:06:34 ago. (Use '!kill 115' to kill it.)' and at the tensorboard just going blank and not found
@@seonahbae4377 try %load_ext tensorboard %tensorboard --logdir ./runs/ -->HPARAMS and then you will see table view, parallel coordinates and scatter plott -->click on <parallel coordinates>
I got this error because of loss.backward() .one of the variables needed for gradient computation has been modified by an inplace operation: [torch.FloatTensor [32, 1024]], which is output 0 of ReluBackward0, is at version 1; expected version 0 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True).
@@databowlrecipes318 hello, thankyou for your video, but i got this message, please help: ERROR: Could not find a version that satisfies the requirement torch==1.7.0 (from versions: 1.11.0, 1.12.0, 1.12.1, 1.13.0, 1.13.1) ERROR: No matching distribution found for torch==1.7.0 [notice] A new release of pip available: 22.2.2 -> 22.3.1 [notice] To update, run: python.exe -m pip install --upgrade pip
Great Tutorial !!!. But i am having this error in if torch.cuda.is_available(): device = torch.device("cuda") else: device = torch.device("cpu") print(device) model.to(device) error: model not defined Can you please help me out?
Thanks for this awesome video. I need help in combining tar files. How do I combine all the tar files without corrupting the header. Can you provide me link of the dataset used so that I directly download it from there and avoid combining?
