Skip to main content
Cloud / Azure / Products / Azure Machine Learning - ML Platform

Azure Machine Learning - ML Platform

Azure Machine Learning provides an end-to-end platform for training, deploying, and managing machine learning models.

ai-machine-learning
Pricing Model Per compute resources
Availability Global regions
Data Sovereignty EU regions available
Reliability 99.9% SLA

What is Azure Machine Learning?

Azure Machine Learning is a cloud platform for the entire machine learning lifecycle: from data preparation through model training to deployment and monitoring. The platform supports both code-first approaches for data scientists and AutoML for quick experiments.

Azure ML provides managed compute resources, including CPU clusters and GPU instances for training, as well as Managed Endpoints for inference. Integration with MLflow enables open standards for experiment tracking and model registry.

Core Features

  • Managed Compute Clusters for training with automatic scaling
  • AutoML for automated model selection and hyperparameter tuning
  • MLflow integration for experiment tracking and model versioning
  • Managed Endpoints for real-time and batch inference
  • Responsible AI Dashboard for fairness and interpretability

Typical Use Cases

Predictive Analytics: Prediction models for customer churn, demand forecasting, or predictive maintenance.

Computer Vision: Training image recognition models for quality control, medical imaging, or object detection.

NLP and Text Analytics: Sentiment analysis, document classification, or named entity recognition.

Benefits

  • Scalable GPU clusters without infrastructure management
  • Open standards (MLflow, ONNX) avoid vendor lock-in
  • Integration with Azure OpenAI for GenAI scenarios
  • Enterprise features: VNet, RBAC, Private Endpoints

Frequently Asked Questions

What does Azure Machine Learning cost?

Azure ML itself is free. Costs arise for compute (training and inference), storage, and optional features. GPU compute is the largest cost driver.

Can I use custom frameworks?

Yes, Azure ML supports PyTorch, TensorFlow, Scikit-learn, XGBoost, and more. Custom containers can also be used.

How does Azure ML differ from Azure AI Services?

Azure AI Services offers pre-built APIs (Vision, Speech, Language). Azure ML is for training your own models.

Does Azure ML support Foundation Models?

Yes, the Model Catalog contains open-source foundation models like Llama, Mistral, and Phi that can be deployed or fine-tuned.

Integration with innFactory

As a Microsoft Solutions Partner and AI specialist, innFactory supports you with ML projects using Azure Machine Learning. We help with architecture, training, and MLOps.

Contact us for a non-binding consultation on Azure Machine Learning.

Microsoft Solutions Partner

innFactory is a Microsoft Solutions Partner. We provide expert consulting, implementation, and managed services for Azure.

Microsoft Solutions Partner Microsoft Data & AI

Ready to start with Azure Machine Learning - ML Platform?

Our certified Azure experts help you with architecture, integration, and optimization.

Schedule Consultation