Uber's Michelangelo vs. Netflix's Metaflow

  Uber's Michelangelo vs. Netflix's Metaflow Michelangelo Pain point Without michelangelo, each team at uber that uses ML (that’s all of them - every interaction with the ride or eats app involves ML) would need to build their own data pipelines, feature stores, training clusters, model storage, etc.  It would take each team copious amounts of time to maintain and improve their systems, and common patterns/best practices would be hard to learn.  In addition, the highest priority use cases (business critical, e.g. rider/driver matching) would themselves need to ensure they have enough compute/storage/engineering resources to operate (outages, scale peaks, etc.), which would results in organizational complexity and constant prioritization battles between managers/directors/etc. Solution Michelangelo provides a single platform that makes the most common and most business critical ML use cases simple and intuitive for builders to use, while still allowing self-serve extensibi...

Undergraduate Computer Science Assignments

Hey all!

This page will contain links to all of my assignments, which I will post along my journey through to my degree in Computer Science at University of Calgary.  Right now, I'm working with Java and SPARC assembly language programming, and I hope this page grows in content quickly.  Keep checking back for more programs for your pleasure.  Also, feedback is always welcome from anyone who's interested in IT, or in the field.

First Year Java Assignments

Card Match Program

Binary Search Tree For a Text File

Alien chapter 7, Absolute Java solution

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