From Notebook to Production: Deploying ML Models with Confidence.

Transitioning machine learning models from development to production can be challenging. This talk demystifies the deployment process, offering a comprehensive guide to getting your models into production environments securely and efficiently. We'll explore various deployment strategies, including containers, serverless architectures, and dedicated ML platforms. Learn about best practices for monitoring, scaling, and maintaining your models post-deployment. By the end of this session, you'll be equipped with actionable insights and tools to deploy your models confidently and ensure they deliver real-world value.