TensorFlow Serving with Docker for Model Deployment

This 1.5-hour guided project, "TensorFlow Serving with Docker for Model Deployment," equips you with the skills to seamlessly deploy deep learning models using TensorFlow Serving and Docker. With a focus on text classification, you will learn to:

1. Train and export TensorFlow models for text classification
2. Serve and deploy models with TensorFlow Serving and Docker
3. Perform model inference with gRPC and REST endpoints

As organizations increasingly adopt machine learning and AI, the ability to deploy models to production becomes essential for data scientists and machine learning engineers. This project bridges the gap, providing a real-world foundation for pushing TensorFlow models from development to production efficiently. Prior experience with Python and building models with Keras or TensorFlow is recommended.