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Built an AI-powered speech analysis platform combining audio processing, speech recognition, and semantic analysis. Developed the ML pipeline using Whisper and audio features, with a FastAPI AI service and a React/Node.js web application. Implemented MongoDB data storage and JWT-based authentication to provide a complete full-stack application.
The network for creativity
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A good landing page shouldn’t make you work to understand it.
Been working on a new project where the goal was simple:
Make a complex product feel simple, clear, and easy to explore.
Less explaining.
Less clutter.
More visual hierarchy.
A clearer path to the next step.
Still working through the details, but this one is coming together nicely.
Full case study soon.
This pairs well with the Hire Hangar screenshot because the design itself demonstrates the point—you don't need to reveal the whole project yet.
Appreciated @Mehdi Hassan
keep on rocking
The model isn't the product.
The experience is.
A digital runway built with 3D, motion, and a little bit of controlled chaos.
No templates. No static grids. Just fashion translated into an interactive world.
Would you put this on a fashion brand's homepage?
I built this face detection app to run machine learning models directly in the browser inside a clean interactive UI.
Users can upload any photo and get an instant scan. The system draws targeting brackets over the face, maps 68 facial points, estimates age and gender, and shows percentage bars for seven basic emotions. If a photo has more than one person, the app counts them and lets you click through each face to update the readings on screen.
Everything runs on the client side using JavaScript and HTML5. The photos stay on the user's computer and never get uploaded to an external server. The model detects the face position, facial points, age, and emotion expression in one pass. If someone uploads a photo without a visible face or any pics of living creatures other than humans, the app handles the error and updates the status message instead of freezing.
The ragebaiting part was to format and structure out the data so it felt clean and fast. Putting the emotion stats beside the face box makes it easy to read the numbers while looking at the person. No distractions, no drama... Showing the total face count in the corner also helps users know if the model missed anyone in the photo.😊
Looks very futuristic💯