Prerequisites
- Basic Git knowledge
- Understanding of ML workflows
- Basic Python knowledge
- Familiarity with command line
- Interest in managing ML datasets
What Will You Learn
- Why data versioning is important
- How DVC works with Git
- Tracking datasets in ML projects
- Creating reproducible ML pipelines
- Managing experiment results
- Remote storage for datasets
- Best practices for ML data management