daemonX10 commented 3 months ago

Pull Request for ML-Crate 💡

Issue Title: End-to-end Sensor Fault Detection #644

Info about the related issue (Aim of the project) : The Sensor Fault Detection system is designed to monitor sensors and detect any faults. It uses advanced algorithms to ensure the accuracy and reliability of sensor data.
Name: Damodar Yadav
Email ID for further communication: damodarryadav@gmail.com
GitHub ID: https://github.com/daemonX10
Idenitfy yourself: SSOC'24 contributor

Closes: #644

Describe the add-ons or changes you've made 📃\

Make the Model for Predication of condication of Sensor , it's good/Bad need replacement or not . I used various model for this and xgboost model out perform other and then done hyperparameter tunning.
Create PipeLine for data Ingestion , Data transformation , Model evaluation , Predication
Created Web app using Flask , django and Tailwind css and more

What sort of change have you made:

[ ] Bug fix (non-breaking change which fixes an issue)
[✓] New feature (non-breaking change which adds functionality)
[ ] Code style update (formatting, local variables)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

How Has This Been Tested? ⚙️

Describe how it has been tested

Describe how have you verified the changes made

Checklist: ☑️

[✓] My code follows the guidelines of this project.
[✓] I have performed a self-review of my own code.
[✓] I have commented my code, particularly wherever it was hard to understand.
[✓] I have made corresponding changes to the documentation.
[✓] My changes generate no new warnings.
[✓] I have added things that prove my fix is effective or that my feature works.
[✓] Any dependent changes have been merged and published in downstream modules.

github-actions[bot] commented 3 months ago

Our team will soon review your PR. Thanks @daemonX10 :)

daemonX10 commented 3 months ago

@abhisheks008 changes done . i have make new folder for web part and remaining dataset , model and notebook along with image in main folder

abhisheks008 commented 3 months ago

In the web app folder create a README file (template: https://github.com/abhisheks008/ML-Crate/blob/main/.github/web-app-readme-template.md) and put a demonstration video of the working of the web app. Also attach the same video in the README so that others can view that easily.

daemonX10 commented 3 months ago

@abhisheks008 done those change in web readme file

abhisheks008 commented 3 months ago

Just copy the demo video from your local system and paste the same inside the README so that it can be embedded inside the README and can also be viewed easily. @daemonX10

daemonX10 commented 3 months ago

that video is available in img folder already @abhisheks008

abhisheks008 commented 3 months ago

Although it is available in the img folder, we can not view that video directly. That's why I told you to do so in the above comment.

daemonX10 commented 2 months ago

@abhisheks008 added direct video embedding in readme

abhisheks008 commented 2 months ago

Video is not visible. @daemonX10

Harshit-code-tech commented 2 months ago

i have 4 things to ask... 1) this is for local right??? how about web service deployment....it would be nice if you do that after submitting and completing on this...ofc on render or.. vercel..

2) i would like to know theway of it's working...it must be really frustating to make.. because of tons of errors...right?

3) what are it's limitations.. ? 4) what's the best accuracy with val_loss?

abhisheks008 commented 2 months ago

i have 4 things to ask...

this is for local right??? how about web service deployment....it would be nice if you do that after submitting and completing on this...ofc on render or.. vercel..

i would like to know theway of it's working...it must be really frustating to make.. because of tons of errors...right?

what are it's limitations.. ?

what's the best accuracy with val_loss?

@daemonX10 will explain this very well, as he is the one who is developing the whole thing. About the web app part, it is hosted in local. As a beginner when you are building a college project, locally hosted web app is enough, because majority of the college students used to take help from this project repository.

daemonX10 commented 2 months ago

i have 4 things to ask...

this is for local right??? how about web service deployment....it would be nice if you do that after submitting and completing on this...ofc on render or.. vercel..

i would like to know theway of it's working...it must be really frustating to make.. because of tons of errors...right?

what are it's limitations.. ?

what's the best accuracy with val_loss?

Local deployed, i have deployed multiple projects on render, you could ask me, although i have added all steps in Readme and the reason i don't deployed it, cause i not that much complex project.

NO, it's a simple project nothing more
Limitation, train on small dataset,
Val_loss check notebook

daemonX10 commented 2 months ago

IMG_20240707_194929 @abhisheks008 see, i have added video

Harshit-code-tech commented 2 months ago

@daemonX10 to upload a video.. first go to any code issue tab.. in there from your local upload the video in chatbox...then github will provide a link..paste that in your readme note...

to check if your work or not.. go to file changed... in that .. go the the desired file... and click on 3 dots in right cornor of that particular...then view file...and then you can see what is visible to public

also... when used xgboost well..there is no issue in using decision tree..but it's no use when using xgboost...as it is the upgraded version of that

abhisheks008 commented 2 months ago

@daemonX10 to upload a video.. first go to any code issue tab.. in there from your local upload the video in chatbox...then github will provide a link..paste that in your readme note...

to check if your work or not.. go to file changed... in that .. go the the desired file... and click on 3 dots in right cornor of that particular...then view file...and then you can see what is visible to public

also... when used xgboost well..there is no issue in using decision tree..but it's no use when using xgboost...as it is the upgraded version of that

Upload the video as mentioned @daemonX10

daemonX10 commented 2 months ago

https://github.com/abhisheks008/ML-Crate/assets/115637298/7712a38e-94b3-4463-ba65-c34f3e3a484d

"https://github.com/abhisheks008/ML-Crate/assets/115637298/7712a38e-94b3-4463-ba65-c34f3e3a484d" change the link @abhisheks008

abhisheks008 commented 2 months ago

Still the video is not visible.

daemonX10 commented 2 months ago

Do check now @abhisheks008, it showing

abhisheks008 commented 2 months ago

Hi @daemonX10 have you registered in the OSLead portal?

daemonX10 commented 2 months ago

What is OSLead? @abhisheks008

abhisheks008 commented 2 months ago

What is OSLead? @abhisheks008

You are part of SSOC and you don't know OSLead? Check out the announcement channel of the SSOC Discord server and register yourself in OSLead for leader board.

@daemonX10

abhisheks008 commented 2 months ago

What is OSLead? @abhisheks008

You are part of SSOC and you don't know OSLead? Check out the announcement channel of the SSOC Discord server and register yourself in OSLead for leader board.

@daemonX10

Hi @daemonX10 have you done the needful?

daemonX10 commented 2 months ago

I'm forgot that, can you give me link please @abhisheks008

abhisheks008 / ML-Crate

Sensor fault detection #657

Pull Request for ML-Crate 💡

Issue Title: End-to-end Sensor Fault Detection #644

Describe the add-ons or changes you've made 📃\

What sort of change have you made:

How Has This Been Tested? ⚙️

Checklist: ☑️