👩💻 Gender Classification Model
A lightweight Gender-Classification image model trained with Google’s Teachable Machine to quickly test service speed and large-scale image processing performance.
✨ Overview
This model was built as a practical benchmark for evaluating how well the service handles many image inputs under real usage conditions. The goal was not only classification, but also measuring throughput, responsiveness, and stability when processing image-heavy workloads.
🚀 What it’s for
- Fast image classification testing.
- Performance checks on bulk image processing.
- Service stress testing with a simple ML workflow.
- Quick prototyping without a complex training pipeline.
🛠️ Training Setup
The model was trained through Google Teachable Machine, using an image classification project workflow. In that flow, images are grouped into classes, the model is trained in-browser, and then exported or shared as a link.
📌 Notes
- This project is intended for benchmarking and experimentation.
- Model behavior depends on the quality and diversity of the training images.
- Teachable Machine is useful when you want rapid iteration and a straightforward deployment path.
🎯 Result
A simple, practical image model for testing how quickly a service can classify many images while staying easy to demo, share, and iterate on.