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ANA 680 Machine Learning

Module 3 Required Learning Resources

    1.  

Gears. C (2022). Docker Fundamentals for Beginners. Packet publishing. Chapters 1, 2, 3.  This video book provides an introductory presentation of virtualization and how it compares to containerization and docker.

Emmanuel Raj (2021). Engineering MLOps (O’Reilly). Chapters 7, 8, 9, 10. Chapters discuss cloud computing services for machine learning.

    1.  

Amazon SageMaker Example Notebooks: An example of ML project for Customer Churn Prediction With XGBOOT on AWS SageMaker.: https://sagemaker-examples.readthedocs.io/en/latest/index.html An

Learn Docker containers (O’Reilly). A video lesson on docker containers

https://learning.oreilly.com/videos/learn-docker-containers/50103VIDEOPAIML.

Module 3 Optional Resources

Machine Learning Container Templates(mlt): https://github.com/tonyreina/mlt  A lesson on containerization and available built-in containers

DevOps Essential on AWS:  http://www.devopsessentialsaws.com/ notes on AWS cloud services for application development

Introduction to Cloud Computing for Machine Learning Beginners: https://www.analyticsvidhya.com/blog/2022/01/introduction-to-cloud-computing-for-machine-learning-beginners/ An article on could services for machine learning projects.

Multi-Cloud Onboarding with Cloud Computing: https://learning.oreilly.com/videos/cloud-computing-with/60650VIDEOPAIML/60650VIDEOPAIML-c1_s1/   A comprehensive lesson on ML development and pipeline automation on Linux systems. Resource 4 is a prerequisite for this lesson.