Containerization of ML Workloads to Increase Data Science Productivity


One of the challenges with Machine Learning and Data Science projects is standardizing compute environments so that teams will start with approved packages and libraries that are functional together. Cloudera has developed a pluggable approach to this which gives users access to a blueprint to create custom ML Runtime that consists of not just language specific libraries, but also a compute kernel or OS and partner content. Cloudera is open sourcing these ML Runtimes as a way to promote tighter integration with partners and to make it easier for customers to start from their own approved images.


Alex Bleakley is a Senior Product Manager at Cloudera for production machine learning and MLOps, as well as for machine learning in private cloud. He was formerly a Machine Learning Solutions Architect, working with Cloudera customers to build machine learning applications. Alex graduated in mathematics, and spends his personal time traveling, hiking, and playing soccer.

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