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Learn how to quickly set up a machine learning environment in this 28-minute workshop presentation that demystifies the often overwhelming process of getting started with data science. Discover how to overcome common challenges like tool incompatibility, versioning constraints, and difficult upgrades that typically slow down AI enthusiasts. Follow along as Canonical's Michal Hucko demonstrates how to deploy and run essential open source tools including MLflow and Jupyter Notebooks at no cost. Get hands-on guidance for establishing a fully functional open source machine learning environment that will have you ready to build models in minutes rather than hours. Master the fundamental initial steps needed before beginning any data science project while learning to leverage powerful open source tooling efficiently.
