Sharing data science work can be messy. Learn how to use Docker—the popular tool for deploying and managing apps as containers—to more efficiently share machine learning models.
- [Jonathan] Do you have to share you work frequently with business stakeholders or other colleagues so that they can reproduce your results? Or have you had the problem with code working on you machine and then it seems to blow up on someone else's computer? Docker might just be what you're looking for. Docker and containers are becoming so popular that you'll find official images for various Linux distributions, databases and deep learning frameworks. Hi, I'm Jonathan Fernandes, and I work in machine learning and AI for a consultancy. Join me on LinkedIn Learning as we look at Docker from scratch.
- Why Docker is gaining prominence
- Running a container
- Docker under the hood
- Working with Dockerfiles
- Uploading images to Docker Hub
- Common use cases for Docker