Microsoft Azure
azure.microsoft.com › en-us › products › machine-learning
Azure Machine Learning - ML as a Service | Microsoft Azure
Build machine learning models in a simplified way with machine learning platforms from Azure. Machine learning as a service increases accessibility and efficiency.
Microsoft Learn
learn.microsoft.com › en-us › azure › machine-learning › overview-what-is-azure-machine-learning
What is Azure Machine Learning? - Azure Machine Learning | Microsoft Learn
After you use up the credits, you can keep the account and use free Azure services. Your credit card isn't charged unless you explicitly change your settings and ask to be charged. Machine Learning is for individuals and teams implementing MLOps within their organization to bring ML models into production in a secure and auditable production environment.
Is Azure ML good today ?
What do you mean exactly with "build an AI model from scratch"? You don't have to use anything drag & drop. Everything works via their api/sdk. It's basically a collection of tools that are commonly used (or are similar to) in ML (ops). Preprocessing/training/evaluation you could do using their pipelines, and you can even provide your own docker images / environments / etc. More on reddit.com
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November 29, 2024Azure ML - Two models loaded in one scoring script? : AZURE
Hey, Getting to the point --, is it possible to load two different tensorflow models in one scoring script, and invoke each at a given time... More on old.reddit.com
[D] Should we trust cloud ML platforms (aws, azure, gcp)?
If you are working with data that sensitive you should have IT security professionals on staff to answers these kinds of questions. If you have to ask, you shouldn't be setting the data security policy. That said, AWS/Azure/GCP each do tens of billions of dollars in revenue per and they aren't going to throw that away to have a peak at your data. You are far more likely to lose your data in a hack, so get your policies sorted out. More on reddit.com
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November 11, 2020Azure ML - what are people's experiences?
Is probably the worst ML service of the major cloud providers: Documentation is crappy, confusing and some times outdated (real mess with passing data objects between pipeline steps) Data drift and model monitoring capabilities extremely limited and in preview since 3 years ago. Total mess with AzureML SDK 2.0. Im sorry microsoft but I will not have my ml pipelines as yaml files. This is delusional. Also neither ChatGPT can answer questions about this version of the SDK because literally no one is using it.... 2 years behind for a centralized model registry (now in preview) Lack of integration between model registry events and azure devops (you need to create a custom azure function to listen to this events and then trigger your CI pipelines). There is an extension for this but it does not work with multiple models. This is important because if your models take more than 6h to train the CI pipelines will fail in DevOps if you use MS Hosted Agents. So deacoplating the CD part from the model generation is usually a good idea. Running spark is a lotery (now in preview again). Other alternatives like SageMaker have allowed you to do that since 2019. There is an unsupported library called RayOnAML to run ray in AML. Is bullshit, it doesn't work in an stable manner. Constant failure of VSCode connection to azureML instances, I recommend you to use JupyterLab (despite of being not optimal) as if you use notebooks with VSCode they will disconnect time to time and you will have to reload everything again. Lack of spot GPU instances (the fail 70% of the time). AML pipelines do not have conditionals, you will always need a high level orchestrator (ADF/LogicApps) to orchestrate complex workflows. I could probably write a blog post with thousands of bad product decisions, unresolved bugs and lack of functionalities. Under any circumstances I will choose this service. PS: I am a senior data scientist with a couple of cloud certifications and strong software designs pattern knowledge and MLOps. I have put more than 7 systems in production with AML. More on reddit.com
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December 29, 2021When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
coursera.org
coursera.org › browse › data science › machine learning
Microsoft Azure Machine Learning | Coursera
How long will it take to complete this course?
You should expect to spend at least an hour every week for four weeks to complete all aspects of this course.
coursera.org
coursera.org › browse › data science › machine learning
Microsoft Azure Machine Learning | Coursera
What will I learn from this course?
Machine learning is at the core of artificial intelligence, and many modern applications and services depend on predictive machine learning models. Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier. In this course, you will learn how to use Azure Machine Learning to create and publish models without writing code.
coursera.org
coursera.org › browse › data science › machine learning
Microsoft Azure Machine Learning | Coursera
Videos
14:03
Performing Automated Machine Learning with AzureML - YouTube
12:50
What Does Azure ML Actually Give Us? - YouTube
15:14
Azure Machine Learning: the Overview - YouTube
45:09
Basic first project! Azure Machine Learning Easy Getting Starting ...
15:54
Training a Model with the Azure ML Designer - YouTube
47:18
Getting started with Azure Machine Learning Studio - YouTube
Microsoft Learn
learn.microsoft.com › en-us › azure › machine-learning
Azure Machine Learning documentation | Microsoft Learn
Train and deploy machine learning models with Azure Machine Learning. Get started with quickstarts, explore tutorials, and manage your ML lifecycle with MLOps best practices.
Microsoft Azure
azure.microsoft.com › en-us › products › category › ai
AI and Machine Learning - Azure Services | Microsoft Azure
Find AI and machine learning services for your needs and create the next generation of applications using Azure capabilities for any developer and scenario.
DataCamp
datacamp.com › tutorial › azure-machine-learning-guide
A Beginner's Guide to Azure Machine Learning | DataCamp
March 21, 2024 - Explore Azure Machine Learning in our beginner's guide to setting up, deploying models, and leveraging AutoML & ML Studio in the Azure ecosystem.
Microsoft Azure
azure.microsoft.com › en-us › pricing › details › machine-learning-studio
Pricing – Machine Learning Studio (Classic) | Microsoft Azure
Azure Machine Learning is a separate enterprise-grade service that supports the end-to-end machine learning lifecycle, with a wide range of productive experiences to build, train and deploy models, including designer for ...
Microsoft Learn
learn.microsoft.com › en-us › azure › architecture › ai-ml › guide › data-science-and-machine-learning
Overview of Microsoft Machine Learning Products and Technologies - Azure Architecture Center | Microsoft Learn
ML.NET provides various levels of interoperability with popular frameworks like TensorFlow and ONNX for training and scoring machine learning and deep learning models. For resource-intensive tasks like training image classification models, you can use Azure to train your models in the cloud.
Coursera
coursera.org › browse › data science › machine learning
Microsoft Azure Machine Learning | Coursera
July 5, 2021 - IT professionals interested in learning about the types of solutions artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. Working IT professionals looking for additional skills or credentials to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.
Microsoft Learn
learn.microsoft.com › en-us › shows › ai-show › azure-machine-learning-studio
Azure Machine Learning Studio | Microsoft Learn
The Azure Machine Learning studio is a new immersive web experience for managing the end-to-end lifecycle. The new web experience brings all of the data science capabilities for data scientists and engineers, across diverse skill levels from ...
RAPIDS
docs.rapids.ai › deployment › stable › cloud › azure › azureml
Azure Machine Learning — RAPIDS Deployment Documentation documentation
Although it is possible to install Azure Machine Learning on your local computer, it is recommended to utilize Azure’s ML Compute instances, fully managed and secure development environments that can also serve as a compute target for ML training.
Wikipedia
en.wikipedia.org › wiki › Microsoft_Azure
Microsoft Azure - Wikipedia
3 weeks ago - Microsoft Azure Machine Learning (Azure ML) provides tools and frameworks for developers to create their own machine learning and artificial intelligence (AI) services.
Microsoft Learn
learn.microsoft.com › en-us › training › paths › explore-azure-machine-learning-workspace
Explore and configure the Azure Machine Learning workspace - Training | Microsoft Learn
Explore and configure the Azure Machine Learning workspace, its resources and its assets. Explore which developer tools you can use to interact with the workspace, focusing on the CLI and Python SDK v2.
Microsoft Learn
learn.microsoft.com › en-us › shows › dev-intro-to-data-science › what-is-azure-machine-learning-16-of-28
What is Azure Machine Learning? (16 of 28) | Microsoft Learn
Azure Machine Learning is a cloud-based environment you can use to train, deploy, automate, manage, and track your machine learning models. You can use Azure Machine Learning for any kind of machine learning, from classical ML to deep learning, ...
Reddit
reddit.com › r/datascience › is azure ml good today ?
r/datascience on Reddit: Is Azure ML good today ?
November 29, 2024 -
Hi, to give a bit of context I work in a medium sized company that want to start some ML projects. We are already in the azure ecosystem with some data, webapps, powerBI and stuffs, we are now seeking for a ML cloud provider to do all our MLops. As I can see azure ML can be a bit frustrating, what are your thought on it nowadays ?
I am more a coding guy and don't like as much drag&drop tools, can we build an ai model from scratch with VS code integration or whatever (preprocessing/training/evaluation)?
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What do you mean exactly with "build an AI model from scratch"? You don't have to use anything drag & drop. Everything works via their api/sdk. It's basically a collection of tools that are commonly used (or are similar to) in ML (ops). Preprocessing/training/evaluation you could do using their pipelines, and you can even provide your own docker images / environments / etc.
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One of my old firms were using Azure Data Bricks. Smooth Integration with MLFlow. So all your MLOps work becomes pretty easy. Also it's pretty efficient with large scale data as well.
Machinelearningartificialintelligence
machinelearningartificialintelligence.com › blog › azuremachinelearningsolutions.html
Azure Machine Learning Solutions | Azure ML
April 8, 2024 - Azure Machine Learning provides tools to: Facilitate collaboration via shared notebooks, compute resources, serverless compute, data, and environments. Develop models ensuring fairness, explainability, tracking, and auditability to meet lineage and audit compliance requirements.
Medium
valentinaalto.medium.com › introduction-to-azure-machine-learning-13143ccd19b2
Introduction to Azure Machine Learning | by Valentina Alto | Medium
November 28, 2022 - Introduction to Azure Machine Learning Democratizing Data Science Azure Machine Learning (AML) is a cloud service for accelerating and managing the machine learning project lifecycle. So once the …
Microsoft Learn
learn.microsoft.com › en-us › azure › machine-learning › foundry-models-overview
Explore Microsoft Foundry Models in Azure Machine Learning - Azure Machine Learning | Microsoft Learn
The models are made available through Azure Machine Learning registries that enable ML first approach to hosting and distributing Machine Learning assets such as model weights, container runtimes for running the models, pipelines for evaluating ...
Coursera
coursera.org › browse › computer science › software development
Microsoft AI & ML Engineering Professional Certificate | Coursera
Category: Artificial Intelligence and Machine Learning (AI/ML)Artificial Intelligence and Machine Learning (AI/ML) ... This course provides hands-on experience with Microsoft Azure's AI and ML services. You will learn to set up, manage, and ...
Bloomcs
bloomcs.com › home › blog › what is azure machine learning: a beginneru2019s guide
What is Azure Machine Learning: Beginner’s Guide
August 23, 2025 - It is a service intended for data scientists, developers, and business users possessing an extensive set of capabilities that support the entire machine learning lifecycle. Using compute power at its disposal alongside open-source tools and Azure services to the fullest, ML helps organizations build scalable, secure, and efficient AI solutions.
The Knowledge Academy
theknowledgeacademy.com › blog › microsoft-azure-machine-learning
Utimate Guide For Microsoft Azure Machine Learning
October 18, 2025 - Azure ML is an end-to-end cloud-based platform for predictive analytics that provides data scientists with a streamlined working experience. Azure ML was introduced by Microsoft to simplify the workflow and visual experience for users, thus ...