Deploying Scalable Machine Learning Projects in Production

Student: Fedorov Pavel

Supervisor: Sergey Lisitsyn

Educational Programme: Big Data Systems (Master)

Year of Graduation: 2021

The number of machine learning applications is constantly growing, that leads industry to new challenges. Building a predictive model may seem a simple task, but the final product is a full machine learning pipeline, that should be efficiently engineered, validated, monitored, and correctly transferred from development to production environment, to be operationalized. Manual maintenance is becoming impossible with growing scale, and there is a need to automize machine learning steps using practices and principles from software development and DevOps fields.

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