Dive into Docker fundamentals and machine learning in this comprehensive 26-minute tutorial. Explore containers, images, and Dockerfiles through clear visualizations and hands-on examples. Understand the logic behind Docker components, their problem-solving capabilities, and the consequences of not using them. Develop a simple machine learning program using Huggingface Transformers library, build a custom Docker image based on Jupyter Tensorflow Notebook, and learn to deploy projects to DockerHub. By the end, gain practical experience in creating a video captions translating software and acquire a thorough understanding of Docker, regardless of prior programming experience. Topics covered include Docker installation, image management, container operations, MNIST dataset handling with Tensorflow, Docker Compose usage, Dockerfile creation, text translation with Transformers, and pushing images to remote repositories.