Saturday, October 20 • 4:30pm - 5:00pm
Choosing the Right Cloud, a Machine Learning Approach

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As cloud services have grown in maturity and offerings, the differentiations between them has shrunk. For example, many CSPs now provide capabilities to host and run Jupyter Notebooks for Data Science workloads, but what makes one different than the other? As a data scientist, I wanted to see if it would be possible to classify respective clouds by using machine learning. An effect dataset and model could provide insights to the differences in userbases among clouds, and could help those new to developing in cloud environments a resource to choose a cloud in which other users having similar coding styles, interests, and needs

avatar for Nick Acosta

Nick Acosta

Developer Advocate, IBM
Before becoming a Developer Advocate at IBM, Nick studied computer science at Purdue University and the University of Southern California, and was a high performance computing consultant for Hewlett-Packard in Grenoble, France. He now specializes in machine learning and interacting... Read More →

Saturday October 20, 2018 4:30pm - 5:00pm
Ballroom # 403B