This full-stack computer vision course provides a complete roadmap for building, training, and deploying object detection models using TensorFlow, Python, and TensorFlow.js with React. It is designed for developers who want to go beyond model building and create real-world AI-powered applications.
The course begins with setting up the TensorFlow Object Detection API from scratch, guiding you through the installation and configuration process. You will then learn how to build custom object detection models, including collecting and labeling your own data.
A major part of the course focuses on real-time applications such as face mask detection and sign language recognition using deep learning models like MobileNet SSD. These projects demonstrate how computer vision can be applied in practical scenarios.
The course also covers evaluation metrics such as mean average precision (mAP) and recall, helping you measure model performance accurately.
In the second half, you will transition to full-stack development by deploying models into web applications using TensorFlow.js and React. You will build interactive, real-time AI apps that run directly in the browser.
By the end of this course, you will be able to build end-to-end computer vision systems, from data preparation and model training to deployment in scalable web applications.
