• Continuous Integration (CI) and Continuous Deployment (CD) pipelines for Machine Learning (ML) applications
• Importance of CI/CD in ML lifecycle
• Designing CI/CD pipelines for ML models
• Automating model training, deployment, and monitoring
• Overview of tools and platforms used for CI/CD in ML
tensorflow jupyter):
Download the training zip file from drive, extract it
docker run --rm -it -e JUPYTER_ENABLE_LAB=yes -p 8888:8888 -v /Users/foo/Learn/python/training:/home/jovyan/ jupyter/tensorflow-notebook:latest
Download the Docker image and show the help text to make sure it works.
docker run --rm -v `pwd`:/ne/input -it alexjc/neural-enhance --help
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