MLOps 2-weeks assessment

MLOps enhances the machine learning model training process by reducing infrastructure costs, speeding up production rollouts, and enabling the management of thousands of models simultaneously. Utilizing Azure-based tools and pipelines, ELEKS helps you identify gaps and accelerate model performance, selection, monitoring, and versioning. By following MLOps best practices and principles, and using open-source components along with Azure-specific services, ELEKS will help you improve the quality and reliability of your ML solutions within the Azure Cloud.

Additionally, MLOps facilitates seamless collaboration between data scientists and operations teams, ensuring efficient model lifecycle management. Azure's robust security features protect your ML models throughout their lifecycle. With automated workflows, MLOps on Azure supports continuous integration and continuous deployment (CI/CD) of ML models, leading to faster innovation and reduced time to market. Azure's scalable infrastructure supports large-scale model training and deployment, making it ideal for enterprises looking to leverage machine learning at scale.

ELEKS provides a 2-week MLOps assessment conducted by our AI/ML experts. This assessment will produce a comprehensive report that includes:

• Evaluation of current model deployment practices.
• A gap analysis based on MLOps best practices.
• Tailored recommendations for frameworks and tools to optimize your MLOps pipeline in the Azure Cloud.

Assessment Roadmap: Week 1: Investigating current infrastructure and pipelines to identify gaps and analyze pain points. Week 2: Preparing a roadmap with our recommendations and gap analysis, along with potential solutions. Presenting the findings to the client.