Description

This session on Docker AI explores how containerization is transforming AI development and deployment. Learners will discover how to package, run, and scale AI models effortlessly using Docker, ensuring portable, reproducible, and efficient workflows. The module covers practical insights into dockerizing TensorFlow and PyTorch models, creating modular pipelines, and integrating with Kubernetes for scalable AI deployments. Participants will also learn the key advantages of Docker, including faster experimentation, consistent environments, improved resource utilization, and seamless deployment across platforms. By the end of the session, learners will be equipped to leverage Docker to accelerate AI projects and deliver reliable, production-ready solutions.