Shypd.aiThe largest open index of AI toolsdtu_mlops is an Open Source tool that provides exercises and supplementary material for a Machine Learning Operations course. It offers hands-on experience with frameworks for organizing, scaling, monitoring, and deploying ML models.
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dtu_mlops is an open-source repository designed for the Machine Learning Operations course at DTU, providing comprehensive exercises and supplementary materials. It aims to introduce students to essential coding practices for organizing, scaling, monitoring, and deploying machine learning models in both research and production settings. The repository offers hands-on experience with various frameworks, both local and cloud-based, for large-scale machine learning. Key learning objectives include efficient code organization, reproducibility through containerized applications, version control for collaboration, continuous integration and machine learning, debugging, profiling, visualization, and monitoring of experiments. It also covers using cloud computing services for scaling experiments, distributed training paradigms, and deploying models locally and in the cloud. The course material is freely available under the Apache 2.0 license.
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