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Name: Ayush Bansal

Type: User

Hi 👋, I'm Ayush Bansal

I am a final year B.Tech undergrad and a programmer. A passionate and dedicated developer with a flair for crafting elegant and efficient digital experiences. My journey in the world of technology has been a rewarding one, and I can't wait to share a glimpse of it with you.

At the heart of my expertise lies Flutter, a versatile and powerful framework that I've mastered inside-out. My ability to create stunning, cross-platform applications with Flutter showcases my commitment to staying at the forefront of modern app development. But that's not where my skills end. I'm well-versed in a variety of programming languages, frameworks, tools and other tech stuff.

🌱 I’m currently learning cross-platform application development
👯 I’m looking to collaborate on Flutter projects
📫 How to reach me: [email protected]

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Ayush Bansal's Projects

adstack-assignment

algos-for-all-amigos

This repository consists an implementation of the Algorithms encountered in Computer Science, Physics and Mathematics.

attend-it

Professional Project made at GD College, India. A flutter application which uses device's location to track the attendance of employees of the organization. It also uses Face recognition and Analytics to decrease false attendance.

attendance-application-google-map

Attendance Tracking Application Implementation Using Flutter Google Maps

authenticate-via-tensorflow-facial-recognition-in-flutter

The power of machine learning allows us to change long-standing computing paradigms. One of these is the age-old password-based authentication system common to most apps. With fast real-time facial recognition, we can easily dispense with text-based verification and allow users to log in just by showing their faces to a webcam. In this session, we’ll show how to do this in Flutter, Google’s popular open-source UI toolkit for developing apps for web, Android, iOS, Fuchsia, and many other platforms with a single codebase. We’ll first build a simple authentication-based Android app, and then deploy the Firebase ML Vision model for face ID & image processing; as well as the MobileFaceNet CNN model through TensorFlow Lite for structured verification. Once all these parts are in place, our solution will work seamlessly and can easily be ported to other apps. Pre-requisites: ✅ Android Studio (https://developer.android.com/studio) — you can also use other IDEs/platforms if you’d rather not use Android - Flutter documentation below guides on the same. ✅ Flutter SDK (https://flutter.dev/docs/get-started/install) ----------------------------------------- To learn more about The Assembly’s workshops, visit our website, social media or email us at [email protected] Our website: http://theassembly.ae Instagram: http://instagram.com/makesmartthings Facebook: http://fb.com/makesmartthings Twitter: http://twitter.com/makesmartthings #TensorFlow #Flutter #MachineLearning