This project implements a Face Recognition System using dimensionality reduction techniques such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).
I built a Simple Face Recognition system using Python and a KNN classifier to identify and classify faces from images.
This project taught me a lot about machine learning workflows, image processing, and model training pipelines. I also learned how to turn a machine learning model into a usable product by building a REST API with FastAPI and connecting it with simple web and client interfaces.
One of the biggest challenges was improving accuracy and handling different image conditions, so I added image enhancement and batch training features to make the model more reliable.
I also practiced deployment skills by Dockerizing the project and preparing it for cloud deployment.
Overall, this project helped me connect ML concepts with real-world application development, from training a model all the way to deploying a working system.
Identify and classify faces using trained KNN model
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I’m working on my first project! This is so exciting. I can’t wait to share more updates as I build.
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