MLOps Cockpit: 8-Weeks Implementation

MLOps cockpit , © Copyright [2021], Tata Consultancy Services Limited. All Rights Reserved, on Microsoft Azure provides you the top functionalities of automation and monitoring for all Machine Learning Operations.

The solution levarages multiple Azure services including Azure ML, ADF, Power platform and Azure Devops

Utilizing the power of DevOps and automation enriched functionalities, It allows you to analyze various metrics of the model (to train the model, package the model, validate, deploy and monitor) and perform statistical change in data using data drift which enables you to retrain your model. Top 4 Benefits:

 Enhance your business value: Create end to end ML operation solutions which will scale and speedup AIML development to production cycles and significantly reduce market time. Provide ready platform for reproducible experimentation to achieve optimized solutions in secured manner.  Standardized Environment: Collaborative approach enablement and standardize ML Production environment across business teams. With exceptional monitoring features, you can deliver consistent quality solutions along with keeping a track of versioning with models. Your business can easily enable 360 degree needs of ML Lifecycle.  Better Visibility with Team Connectivity: Better visibility of ML lifecycle for your business by collaborating with various team members (Data Scientist, DevOps, Data Engineer and Business Users) along with keeping track of various versions of code, Data and models.  Cost Optimization: With Event based pipeline automation, enable retraining of models especially when certain business conditions are met. Using MLOps, you can be guaranteed that all your resources are efficiently used and monitored. Also, they are bound to have significant cost benefit over optimized time and resources utilization.