Head of Data science, OutFund
Data Engineering Manager, Microsoft Corporation
Big Data Engineer, Beyond Limits
Director of Business Intelligence , CouponFollow
In this Azure MLOps Project, you will learn to perform docker-based deployment of RNN and CNN Models for Time Series Forecasting on Azure Cloud.
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Business Objective
Machine Learning Operations (MLOps) is based on DevOps principles and practices that increase the efficiency of workflows. For example, continuous integration, delivery, and deployment. MLOps enables the automated management of the end-to-end machine learning lifecycle. The main goal of MLOps is the faster deployment of models in production.
We will be using Azure as our cloud platform. Microsoft Azure provides many robust services in its ecosystem to create an end-to-end MLOps pipeline. In this project, we will be deploying our time-series deep learning model on the Azure cloud platform in a multi-part format.
Aim
To create an MLOps project using the Microsoft Azure platform to deploy a deep learning model in production.
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Prerequisites
It is advisable to have a basic knowledge of the following services to understand the project.
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