Machine learning (ML) is a powerful way to generate insights and predictions from your data, but it also comes with many challenges and complexities. You need to manage your ML code, data, and artifacts, automate your ML workflows, track and compare your ML experiments and metrics, deploy and monitor your ML models, and collaborate and share your ML insights with your team and stakeholders.
All of these tasks require a robust and scalable ML Ops solution that can help you scale your AI initiatives and increase the efficiency, quality, and reliability of your ML solutions in a way that is secured, maintainable, governed and monitored.
Azure Machine Learning is a cloud-based platform that provides end-to-end capabilities for building, training, deploying, and managing ML models. Azure DevOps is a platform for collaborative software development and delivery that integrates with Azure technologies including Azure Machine Learning. Together with Azure DevOps, it allows you to implement best-practice ML Ops to:
Our expert team of big data engineers and data scientists will help you better understand your data, expedite advanced analytics model implementation, and design data lakes and workspaces for data science and research.