AI & Machine Learning Services
Explore Microsoft's comprehensive suite of Artificial Intelligence (AI) and Machine Learning (ML) services designed to empower developers and businesses to build intelligent applications and unlock new insights from data.
From pre-trained models to custom ML development platforms, Microsoft Azure offers the tools and infrastructure you need to integrate AI capabilities seamlessly into your workflows.
Azure AI Services
Azure AI Services provide powerful, cloud-based AI capabilities that are easy to integrate into your applications. These services cover a wide range of AI tasks, including vision, speech, language, decision, and search.
Azure Cognitive Services
A collection of REST APIs and SDKs that enable developers to easily add visual, speech, and language understanding to their applications.
- Vision: Computer Vision, Face API, Form Recognizer
- Speech: Speech to Text, Text to Speech, Speaker Recognition
- Language: Text Analytics, Language Understanding (LUIS), Translator
- Decision: Anomaly Detector, Content Moderator, Personalizer
Azure OpenAI Service
Access cutting-edge large language models (LLMs) like GPT-4 and GPT-3.5-Turbo for natural language generation, summarization, code generation, and more.
- Powerful natural language understanding and generation
- Fine-tuning capabilities for custom models
- Secure and scalable enterprise-grade AI
Azure AI Vision
Leverage advanced computer vision capabilities to analyze images and videos, detect objects, read text, and understand content.
- Image analysis, OCR, and object detection
- Facial recognition and analysis
- Video indexing and analysis
Azure AI Speech
Integrate speech-to-text, text-to-speech, and speech translation into your applications to create more engaging user experiences.
- Real-time speech recognition
- Natural-sounding text-to-speech voices
- Speech translation for global communication
Azure Machine Learning
Azure Machine Learning is a cloud-based environment that you can use to train, deploy, automate, manage, and track your machine learning models. It provides end-to-end ML lifecycle management.
Automated ML (AutoML)
Quickly find the best performing ML model for your data with automated training and feature engineering.
Designer
A drag-and-drop interface for building ML models without writing code.
Notebooks
Integrated Jupyter notebooks for data exploration, model development, and experimentation.
MLOps
Tools and practices for managing the entire machine learning lifecycle, including deployment, monitoring, and retraining.
Getting Started
Ready to build your first AI-powered application? Follow these steps:
- Sign up for Azure: If you don't have an Azure account, create one for free. Learn more about free services.
- Explore Azure AI Services: Browse the available services and choose the ones that fit your needs. Use the Azure Portal to get started.
- Develop with Azure Machine Learning: Set up your Azure ML workspace and begin building, training, and deploying models. Check out the quickstart guides.
- Consult the SDKs and API Documentation: Dive deep into the technical details with comprehensive documentation for all available SDKs and APIs.
Here's a simple example using the Azure AI Vision SDK (Python):
from azure.cognitiveservices.vision.computervision import ComputerVisionClient
from msrest.authentication import CognitiveServicesCredentials
# Replace with your subscription key and endpoint
subscription_key = "YOUR_SUBSCRIPTION_KEY"
endpoint = "YOUR_ENDPOINT"
credentials = CognitiveServicesCredentials(subscription_key)
client = ComputerVisionClient(endpoint, credentials)
image_url = "https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/media/how-tos/Analyze_image.png"
# Analyze image
analysis = client.analyze_image(image_url=image_url, visual_features=["description"])
print("Description:")
if 'description' in analysis and 'captions' in analysis.description:
for caption in analysis.description.captions:
print(f"'{caption.text}' with confidence {caption.confidence:.2f}")
else:
print("No description found.")