End-to-End MLOps in Azure | Azure Machine Learning​

Teams face many challenges when productionalising a machine learning model, like retraining the model quickly to incorporate improvements, keeping track of metrics and parameters, model versioning and comparison, and its deployment. ​ ​ Addressing these challenges effectively is what makes a successful project.​ ​ In this video, we present a seamless, productive way of dealing with these difficulties using the ClearPeaks MLOps (Machine Learning Operations) methodology in Microsoft Azure. ​ ​ We also show you a real customer use case, demonstrating a full, end-to-end implementation of MlOps in Azure.​ For more details, read our blog post: https://bit.ly/4cEKXEg Chapters:​ 00:00 – 04:18 Introduction​ 04:19 – 09:43 MLOps Methodology​ 09:44 – 11:50 Azure Machine Learning​ 11:51 – 19:50 MLOps Example with Azure ML​ 19:51 – 22:09 Wrap-up & Conclusions