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Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
LLMOps with Prompt Flow is a "LLMOps template and guidance" to help you build LLM-infused apps using Prompt Flow. It offers a range of features including Centralized Code Hosting, Lifecycle Management, Variant and Hyperparameter Experimentation, A/B Deployment, reporting for all runs and experiments and so on.
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
This repo has some proposed agenda for Azure Machine Learning related hands-on workshops.
A Repository for the public preview of Responsible AI in AML vNext
Azure Machine Learning CLI V2 in a Day Workshop/Labs.
Azure AI workshops
Sentiment Analysis for Tweets
It is a Thyroid classification app , where we can classify whether the patient having Thyroid or not using some values of given parameters.
Build a predictive model using Azure ML Studio. Demonstrate a working knowledge of setting up experiments on Azure ML Studio. Operationalize machine learning workflows with Azure's drag-and-drop modules.
Developed a web based application for restaurant named "PARADISE"...
Housing Price Prediction Using Machine Learning.
https://gallery.cortanaintelligence.com/Experiment/Covid-19-prediction-two-algos-Predictive-Exp
Project under Future Ready Talent Internship
This Repositoty shown How we use ML tool like AZURE ML to find insight of data
The repo simulates query load, optimizes performance, and offers practical guidance for building data warehouses with Azure Synapse Analytics. 🚀
In this study Boston House Prices were predicted by using Azure Databricks platform. The data includes the home values of Boston in 1970's. Five of the 14 diverse variables were used for this small study. These are: CRIM - per capita crime rate by town RM - average number of rooms per dwelling TAX - full-value property-tax rate per $10,000 LSTAT - % lower status of the population MEDV - Median value of owner-occupied homes in $1000's The value of homes (median house values) variable was used as the label and the number of rooms, crime per capita, property tax rate, and percent of the population considered lower class variables were used as the features. Predictions were made by using linear regression. Apache Spark Notebook in Azure Databricks were used for running the codes during the analyses.
This repo explains all services provide by azure related to AL-ML services.
This repo explains the importance of integrating azure databricks with azure machine learning. Explained in a whole easy way to accomplish it.
template repository for azure machine learnings
Demo application to interact with Azure AI by exploring Automated Machine Learning in Azure Machine Learning.
Azure DevOps pipeline with ARM templates to deploy an Azure ML workspace with resources in a Subscription
Azure Machine Learning Workshop
Dentro del proceso de la ciencia de datos, la limpieza de datos suele ser la etapa que más tiempo consume. A menos que sea necesario por limitaciones fĂsicas, completar toda esta tarea con computo en la nube puede ser una vĂa poco econĂłmica a comparaciĂłn de hacerlo on-premise. En esta ocasiĂłn, aprenderemos como hacerlo a travĂ©s de un simple ejemplo para lidear con valores atĂpicos en un Dataset de AML.
This GitHub Action allows you to connect to your Workspace.
Banking Application MLOps Workflow
The aim of this project is to check if an adult has income exceeding 50k per year based on the census data.For the following project, I have used the Decision Tree (Booster) algorithm to create and train the model. The model is available as an azure model web service.
Examen DP-100: Conception et implémentation d’une solution de science des données sur Azure
This repo contains my practice code for Azure Machine Learning using both SDK v1 and SDK v2. I used the Pima Indians diabetes prediction dataset for this purpose.