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#azureml — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #azureml, aggregated by home.social.

  1. 🚨 CVE-2025-49747: CRITICAL flaw in Azure Machine Learning (CVSS 9.9). Missing authorization lets authorized users escalate privileges over the network. Review access controls & monitor for signs of abuse. No patch yet—follow Microsoft advisories. radar.offseq.com/threat/cve-20 #OffSeq #AzureML #CloudSecurity #CVE2025

  2. 🚨 CVE-2025-49747: CRITICAL flaw in Azure Machine Learning (CVSS 9.9). Missing authorization lets authorized users escalate privileges over the network. Review access controls & monitor for signs of abuse. No patch yet—follow Microsoft advisories. radar.offseq.com/threat/cve-20 #OffSeq #AzureML #CloudSecurity #CVE2025

  3. 🚨 CVE-2025-49747: CRITICAL flaw in Azure Machine Learning (CVSS 9.9). Missing authorization lets authorized users escalate privileges over the network. Review access controls & monitor for signs of abuse. No patch yet—follow Microsoft advisories. radar.offseq.com/threat/cve-20 #OffSeq #AzureML #CloudSecurity #CVE2025

  4. Introduction to LLMOps, a methodology for operationalizing large language models (LLMs) like GPT-4 it involves prompt engineering, fine-tuning, and deploying LLMs for real-world applications. techcommunity.microsoft.com/t5 #LLMOps #AzureML #MicrosoftAI #softcorpremium

  5. Introduction to LLMOps, a methodology for operationalizing large language models (LLMs) like GPT-4 it involves prompt engineering, fine-tuning, and deploying LLMs for real-world applications. techcommunity.microsoft.com/t5 #LLMOps #AzureML #MicrosoftAI #softcorpremium

  6. Introduction to LLMOps, a methodology for operationalizing large language models (LLMs) like GPT-4 it involves prompt engineering, fine-tuning, and deploying LLMs for real-world applications. techcommunity.microsoft.com/t5

  7. Introduction to LLMOps, a methodology for operationalizing large language models (LLMs) like GPT-4 it involves prompt engineering, fine-tuning, and deploying LLMs for real-world applications. techcommunity.microsoft.com/t5 #LLMOps #AzureML #MicrosoftAI #softcorpremium

  8. I want to deploy huggingface.co/flair/ner-engli into my own tenant, either on #AWS or #Azure. huggingface sales is not responding (guess we are too small a fish). any other options that make this sort of deployment easy? we also currently have 2 custom PyTorch models running on #AzureML I would like to move. but I need to use my own cloud tenant.

  9. I want to deploy huggingface.co/flair/ner-engli into my own tenant, either on #AWS or #Azure. huggingface sales is not responding (guess we are too small a fish). any other options that make this sort of deployment easy? we also currently have 2 custom PyTorch models running on #AzureML I would like to move. but I need to use my own cloud tenant.

  10. I want to deploy huggingface.co/flair/ner-engli into my own tenant, either on #AWS or #Azure. huggingface sales is not responding (guess we are too small a fish). any other options that make this sort of deployment easy? we also currently have 2 custom PyTorch models running on #AzureML I would like to move. but I need to use my own cloud tenant.

  11. I want to deploy huggingface.co/flair/ner-engli into my own tenant, either on #AWS or #Azure. huggingface sales is not responding (guess we are too small a fish). any other options that make this sort of deployment easy? we also currently have 2 custom PyTorch models running on #AzureML I would like to move. but I need to use my own cloud tenant.

  12. I want to deploy huggingface.co/flair/ner-engli into my own tenant, either on #AWS or #Azure. huggingface sales is not responding (guess we are too small a fish). any other options that make this sort of deployment easy? we also currently have 2 custom PyTorch models running on #AzureML I would like to move. but I need to use my own cloud tenant.

  13. Latest update to my data science portfolio showcasing various frameworks and running on AWS and Azure. Still have plenty to learn and document for 2023! You can find my articles on medium.com/@manwill

    Portfolio:
    github.com/godot107/public

    Running on AzureML:
    github.com/godot107/azureml-pu

    #datascience #ai #portfolio #machinelearning #aws #azure #awssagemaker #azureml

  14. New blog post is now live as part of #AzureSpringClean 2023 and covers tips for managing your Azure ML costs. Stay tuned for related content over the next week!

    accessibleai.dev/post/azure_ml

    #azure #azureml #machinelearning

  15. New blog post is now live as part of #AzureSpringClean 2023 and covers tips for managing your Azure ML costs. Stay tuned for related content over the next week!

    accessibleai.dev/post/azure_ml

    #azure #azureml #machinelearning

  16. New blog post is now live as part of #AzureSpringClean 2023 and covers tips for managing your Azure ML costs. Stay tuned for related content over the next week!

    accessibleai.dev/post/azure_ml

    #azure #azureml #machinelearning

  17. New blog post is now live as part of #AzureSpringClean 2023 and covers tips for managing your Azure ML costs. Stay tuned for related content over the next week!

    accessibleai.dev/post/azure_ml

    #azure #azureml #machinelearning

  18. New blog post is now live as part of 2023 and covers tips for managing your Azure ML costs. Stay tuned for related content over the next week!

    accessibleai.dev/post/azure_ml

  19. How to train a machine learning model to be analyzed for issues with Responsible AI (Part 2) rodtrent.com/0um

    #Azure #AzureML #AI

  20. How to train a machine learning model to be analyzed for issues with Responsible AI (Part 2) rodtrent.com/0um

    #Azure #AzureML #AI

  21. How to train a machine learning model to be analyzed for issues with Responsible AI (Part 2) rodtrent.com/0um

    #Azure #AzureML #AI

  22. How to train a machine learning model to be analyzed for issues with Responsible AI (Part 2) rodtrent.com/0um

    #Azure #AzureML #AI

  23. How to train a machine learning model to be analyzed for issues with Responsible AI (Part 2) rodtrent.com/0um

    #Azure #AzureML #AI

  24. Deploying machine learning models in production isn’t always the most straightforward thing to do, especially if you’re thinking about pesky things such as security, scalability, and reliability.

    This is why I wrote a short(-ish😊) quickstart on deploying models with #AzureML managed online endpoints which solve "production" concerns like the ones above.

    Read it here: vladiliescu.net/aml-managed-en and let me know what you think.

  25. Deploying machine learning models in production isn’t always the most straightforward thing to do, especially if you’re thinking about pesky things such as security, scalability, and reliability.

    This is why I wrote a short(-ish😊) quickstart on deploying models with #AzureML managed online endpoints which solve "production" concerns like the ones above.

    Read it here: vladiliescu.net/aml-managed-en and let me know what you think.

  26. Deploying machine learning models in production isn’t always the most straightforward thing to do, especially if you’re thinking about pesky things such as security, scalability, and reliability.

    This is why I wrote a short(-ish😊) quickstart on deploying models with #AzureML managed online endpoints which solve "production" concerns like the ones above.

    Read it here: vladiliescu.net/aml-managed-en and let me know what you think.

  27. Deploying machine learning models in production isn’t always the most straightforward thing to do, especially if you’re thinking about pesky things such as security, scalability, and reliability.

    This is why I wrote a short(-ish😊) quickstart on deploying models with #AzureML managed online endpoints which solve "production" concerns like the ones above.

    Read it here: vladiliescu.net/aml-managed-en and let me know what you think.

  28. Deploying machine learning models in production isn’t always the most straightforward thing to do, especially if you’re thinking about pesky things such as security, scalability, and reliability.

    This is why I wrote a short(-ish😊) quickstart on deploying models with #AzureML managed online endpoints which solve "production" concerns like the ones above.

    Read it here: vladiliescu.net/aml-managed-en and let me know what you think.

  29. In my previous post, I explored the integration of ChatGPT with Microsoft Sentinel.
    In this new post, I'll be sharing my experience of integrating ChatGPT with Jupyter Notebook, a popular open-source platform for data analysis.
    The aim of this Notebook is to provide an interface for asking questions to ChatGPT, assisting security analysts in investigating cyber threats with Microsoft Sentinel Notebooks.

    Blog post: medium.com/@antonio.formato/ge

    GitHub repo: github.com/format81/JupyterNot

    Demo: youtu.be/znvy2m97Cb0

    #microsoft #azure #microsoftsentinel #chatGPT #AI #GPT #cybesecurity #Jupiter #jupyternotebook #notebook #python #mysticpy #kql #azureml #cyberthreats #soc #analysts #incidentresponse #cyber #cloud #cloudnative #cloudsecurity #MulticloudMindset

  30. New post: "Interesting Stuff - XMas, New Year 2022, Week 1 2023".

    This post is the "roundup" for holiday period 2022, and week 1 2023. It of a mixed bag of topics:

    * The obligatory post about ChatGPT and creating a Python app.
    * Tinder for Azure Data Explorer - "Find my partner".
    * The big one: Kafka and Flink! I can't help but wonder where this leaves ksqlDB

    Read all about it:

    nielsberglund.com/post/2023-01

  31. New post: "Interesting Stuff - XMas, New Year 2022, Week 1 2023".

    This post is the "roundup" for holiday period 2022, and week 1 2023. It of a mixed bag of topics:

    * The obligatory post about ChatGPT and creating a Python app.
    * Tinder for Azure Data Explorer - "Find my partner".
    * The big one: Kafka and Flink! I can't help but wonder where this leaves ksqlDB

    Read all about it:

    nielsberglund.com/post/2023-01

    #apachekafka #ai #ml #chatgpt #azuredataexplorer #azureml

  32. New post: "Interesting Stuff - XMas, New Year 2022, Week 1 2023".

    This post is the "roundup" for holiday period 2022, and week 1 2023. It of a mixed bag of topics:

    * The obligatory post about ChatGPT and creating a Python app.
    * Tinder for Azure Data Explorer - "Find my partner".
    * The big one: Kafka and Flink! I can't help but wonder where this leaves ksqlDB

    Read all about it:

    nielsberglund.com/post/2023-01

    #apachekafka #ai #ml #chatgpt #azuredataexplorer #azureml

  33. Just posted a guide on using AUTOMATIC1111's #StableDiffusion web UI on #AzureML GPU compute instances.

    Includes:
    1️⃣ Setting up AML GPU instances using the CLI
    2️⃣ Installing the web ui and checkpoints 1.5 and 2.0
    3️⃣ Speed increases with xFormers
    4️⃣ That `--gradio-auth <user>:<pass>` bit that seems quite important if you don't want ppl going through Gradio instances finding yours and using it to generate all kinds of fun stuff.

    It's available here, I think you'll like it:
    vladiliescu.net/stable-diffusi

  34. Just posted a guide on using AUTOMATIC1111's #StableDiffusion web UI on #AzureML GPU compute instances.

    Includes:
    1️⃣ Setting up AML GPU instances using the CLI
    2️⃣ Installing the web ui and checkpoints 1.5 and 2.0
    3️⃣ Speed increases with xFormers
    4️⃣ That `--gradio-auth <user>:<pass>` bit that seems quite important if you don't want ppl going through Gradio instances finding yours and using it to generate all kinds of fun stuff.

    It's available here, I think you'll like it:
    vladiliescu.net/stable-diffusi

  35. RT docs.microsoft.com
    🙋‍♀️ Did you know #VSCode has an extension that helps you to use your Azure Machine Learning resources?
    Sharon Xu has the details.
    Get the extension:
    Learn more on #AzureML:
    msft.it/6019bPOWP
    msft.it/6010bPOWu

    :sys_twitter: twitter.com/docsmsft/status/15