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Deploy a No-code Predictive ML model as a web service with Azure
Machine Learning
MD Shahriyar AL Mustakim
Mitul
Nur Fathiha Tahiat
Seeum
Beta Microsoft Learn Student
Ambassador
Alpha Microsoft Learn Student
Ambassador
Learning
Objectives:
B.Sc in Computer Science and Engineering at
BRAC University, Bangladesh
AWS Community Builder
Beta Microsoft Learn Student Ambassador
@ShahriyarMitul linkedin.com/in/md-shahriyar-al-mustakim-mitul-
B.Sc in Computer Science and Engineering at
BRAC University, Bangladesh
Alpha Microsoft Learn Student Ambassador
Reseach Assistant at OHCRA
Blogger at Porjotonlipi
@NurTahiat linkedin.com/in/nur-fathiha-tahiat-seeum-230b501a5/ @Nur-Seeum
Azure Machine Leaning
Nur Fathiha Tahiat
Seeum
Azure Machine
Leaning
Azure Machine Learning is a cloud service that you can use to train and
manage machine learning models.
It can be used for any kind of machine learning, from classical ml to deep
learning, supervised, and unsupervised learning.
Whether you prefer to write Python or R code with the SDK or work with no-code/low-code options in the studio.
Start training on your local machine and then scale out to the cloud.
AI For Any skill
level
Designer Automated ML Notebooks
Let's Create our first
Classification Model With AML!
https://portal.azure.com/
Tips for managing costs:
• Configure your training clusters for autoscaling: Number of nodes to 0
• Set quotas on your subscription and workspaces: Configure cost limits
• Set termination policies on your training run: Time limit, minimum accuracy
required, etc.
• Use low-priority virtual machines (VM)
• Use an Azure Reserved VM Instance
Extra:
• Don’t forget to stop computing resources
• Delete workspace resources, but not necessarily the workspace
Resources:
• Create no-code predictive models with Azure Machine Learning - Learn | Microsoft Docs
• Create a classification model with Azure Machine Learning designer - Learn | Microsoft Docs
• Azure Machine Learning documentation | Microsoft Docs
• How to select a machine learning algorithm - Azure Machine Learning | Microsoft Docs
• Algorithm & module reference - Azure Machine Learning | Microsoft Docs
• Plan and manage costs - Azure Machine Learning | Microsoft Docs
• Machine Learning Algorithm Cheat Sheet - designer - Azure Machine Learning | Microsoft Docs
• Zero Code AI with Drag-n-Drop Machine Learning – YouTube
• Azure Machine Learning Designer — Taygan
• The Best Way to Start With Azure Machine Learning (soshnikov.com)
• CloudAdvocacy/AzureMLStarter: This is some tutorial to get you started with Azure ML Service
(github.com)

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How to Deploy a No Code Predictive Machine Learning Model as a Web Service with Azure machine Learning

  • 1.
  • 2. Deploy a No-code Predictive ML model as a web service with Azure Machine Learning MD Shahriyar AL Mustakim Mitul Nur Fathiha Tahiat Seeum Beta Microsoft Learn Student Ambassador Alpha Microsoft Learn Student Ambassador
  • 4. B.Sc in Computer Science and Engineering at BRAC University, Bangladesh AWS Community Builder Beta Microsoft Learn Student Ambassador @ShahriyarMitul linkedin.com/in/md-shahriyar-al-mustakim-mitul-
  • 5. B.Sc in Computer Science and Engineering at BRAC University, Bangladesh Alpha Microsoft Learn Student Ambassador Reseach Assistant at OHCRA Blogger at Porjotonlipi @NurTahiat linkedin.com/in/nur-fathiha-tahiat-seeum-230b501a5/ @Nur-Seeum
  • 6. Azure Machine Leaning Nur Fathiha Tahiat Seeum
  • 7. Azure Machine Leaning Azure Machine Learning is a cloud service that you can use to train and manage machine learning models. It can be used for any kind of machine learning, from classical ml to deep learning, supervised, and unsupervised learning. Whether you prefer to write Python or R code with the SDK or work with no-code/low-code options in the studio. Start training on your local machine and then scale out to the cloud.
  • 8. AI For Any skill level Designer Automated ML Notebooks
  • 9. Let's Create our first Classification Model With AML! https://portal.azure.com/
  • 10. Tips for managing costs: • Configure your training clusters for autoscaling: Number of nodes to 0 • Set quotas on your subscription and workspaces: Configure cost limits • Set termination policies on your training run: Time limit, minimum accuracy required, etc. • Use low-priority virtual machines (VM) • Use an Azure Reserved VM Instance Extra: • Don’t forget to stop computing resources • Delete workspace resources, but not necessarily the workspace
  • 11. Resources: • Create no-code predictive models with Azure Machine Learning - Learn | Microsoft Docs • Create a classification model with Azure Machine Learning designer - Learn | Microsoft Docs • Azure Machine Learning documentation | Microsoft Docs • How to select a machine learning algorithm - Azure Machine Learning | Microsoft Docs • Algorithm & module reference - Azure Machine Learning | Microsoft Docs • Plan and manage costs - Azure Machine Learning | Microsoft Docs • Machine Learning Algorithm Cheat Sheet - designer - Azure Machine Learning | Microsoft Docs • Zero Code AI with Drag-n-Drop Machine Learning – YouTube • Azure Machine Learning Designer — Taygan • The Best Way to Start With Azure Machine Learning (soshnikov.com) • CloudAdvocacy/AzureMLStarter: This is some tutorial to get you started with Azure ML Service (github.com)