Operationalisation of Machine Learning Models
Operationalisation of Machine Learning Models


There has been a tremendous growth in the machine learning over the years. With the aid of the cloud, the processing of vast amount of data has enabled data scientists to develop ML models with invaluable insights. Every company is looking gain competitive advantage by trying to use some form of machine learning or artificial intelligence solution. Whether it is to understand their customers’ behavior, shopping habits, or making predictions based on trends and patterns. The level of success varies depending on the quality of the data and how well the models are trained, but the process of architecting the machine learning solution should be as painless as possible.

In this talk we will be looking at various architectural options for operationalizing machine learning models. Including Serverless architectures, ONNX, Containerization and others.

This presentation is intended for Software/Data Architects, Technical Leads, and Data Engineers/Scientists. The presentation aims to build an understanding of various operationalization options, and how it can be applied in the context of machine learning based software development projects. Some general knowledge of data science and machine learning is desirable.


Dr. Mufajjul Ali is Cloud Solution Architect at Microsoft, specializing in Advanced Analytics and AI. He has a Doctorate Degree from Southampton University, and Master’s from Birkbeck, University of London. Dr.Ali has over 15 years of Industry & Academic experience and his expertise spans across big data, machine learning and architectures.

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