Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
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Updated
Jun 5, 2024 - Jupyter Notebook
Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
Practical works and homeworks on the subject "Cloud technologies and the use of Microsoft Azure in application development" (25.04.2023 - 08.06.2023) at IT STEP Academy in Kryvyi Rih.
Repo for the "Identifying Weather Patterns using Azure ML and Clustering" hands-on lab.
A collection of projects developed under Azure AI ecosystem.
Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
Repo for the "Building a No-Code Classification Model with Azure Automated ML" hands-on lab.
A variation of the Azure OpenAI chat baseline, altered to be deployed specifically into an application landing zone.
An end-to-end solution to digitize piping and instrument diagrams using Azure Services including Azure Machine Learning and AKS.
Examples and guides for adopting Azure AI
Code and tutorials to create an Azure Machine Learning workspace from the Azure Portal, CLI, SDK and ARM templates.
From idea to production in a day: Leveraging Azure ML and Streamlit to build and user test machine learning ideas quickly (Talk at PyCon DE & PyData Berlin 2024)
Package to provide Slurm/PBS experience on Azure Machine Learning
ML Ops Accelerator: Databricks & Azure Machine Learning Unification
Lung cancer detection using deep learning models
Demo application to interact with Azure AI by exploring Automated Machine Learning in Azure Machine Learning.
Azure MLOps
Este repositório contém o tutorial de como treinei o meu primeiro modelo no Azure Machine Learning.
Successfully established a machine learning model that can accurately predict the sales of a superstore based on various features such as quantity, profit, discount, postal code, etc. The features are mainly associated with order details and customer demographics.
Data-driven exploration of hotel reviews using Python and Azure Machine Learning, uncovering sentiment patterns, geographical trends, and temporal insights for informed decision-making in the hospitality industry.
Demos for various ways of deploying ML models to Azure cloud
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