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Data storage and versioning You need data storage and versioning tools to maintain dataintegrity, enable collaboration, facilitate the reproducibility of experiments and analyses, and ensure accurate ML model development and deployment. Easy collaboration, annotator management, and QA workflows.
The incorporation of an experiment tracking system facilitates the monitoring of performance metrics, enabling a data-driven approach to decision-making. Datadrift and model drift are also monitored. By developing this project under the AI Factory framework, Dialog Axiata could overcome the aforementioned challenges.
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