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Consequently, AIOps is designed to harness data and insight generation capabilities to help organizations manage increasingly complex IT stacks. Primary activities AIOps relies on big data-driven analytics , ML algorithms and other AI-driven techniques to continuously track and analyze ITOps data.
The repository also features architecture specifically designed for Computer Vision (CV) and Natural Language Processing (NLP) use cases. Security: We have included steps and best practices from GitHub’s advanced security scanning and credential scanning (also available in Azure DevOps) that can be incorporated into the workflow.
This architecture design represents a multi-account strategy where ML models are built, trained, and registered in a central model registry within a data science development account (which has more controls than a typical application development account). He is passionate about Statistics, NLP and Model Explainability in AI/ML.
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