Added On-Device-ML folder and Relevent Project to the Repo

[Ashok-Kumar-dharanikota]

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Closes: #65 this will be closed through this PR.

Describe the changes you've made

Added On-Device ML for Digit Classification Model
On-device Machine Learning is when you perform inference with models directly on a device (e.g. in a mobile app or web browser). The ML model processes input data—like images, text, or audio—on the device rather than sending that data to a server and doing the processing there. In this, I created a simple Digit Classification model and converted the ML model into tensorflow lite model and Deployed into Android Application.

Type of change

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?

I have tested the machine learning model and ML Android Application on my own system and mobile, and as a proof, I have added the images.

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 tests that prove my fix is effective or that my feature works.
• Any dependent changes have been merged and published in downstream modules.

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