Machine learning is a data science technique that allows computers to use existing data to forecast future behaviours, outcomes, and trends. By using machine learning, computers learn without being explicitly programmed. Azure Machine Learning service provides a cloud-based environment you can use to develop, train, test, deploy, manage, and track machine learning models. We will be using the Azure DevOps project for build and release pipelines along with Azure ML services for ML/AI model management and operationalization. We will write code and pipeline definition for a machine learning project demonstrating how to automate the end to end ML/AI project. The build pipelines include DevOps tasks for data sanity test, model training on different compute targets, model version management, model evaluation/model selection, model deployment as real-time web service, staged deployment to QA/prod, integration testing and functional testing.
Jayesh Bapu Ahire is an organizer of the Pune Elasticsearch User Group and Pune AWS User Group. Jayesh is an AI Researcher doing research on NTM’s and Distributed Neural Computers with renowned universities. He is a freelance AWS consultant. Jayesh has authored books on Neural Networks, Reinforcement Learning, and Simulation Hypothesis. He writes a technical blog and his articles are published in many renowned publications. He has been awarded a title of Twilio Champion by Twilio and Most Valuable Blogger by Dzone.
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