AWS MACHINE LEARNING SERVICES

Lets learn about the different sets of various machine learning services that are being offered by AWS in their cloud portal

AMAZON MACHINE LEARNING

These services provide ready-to-use AI capabilities without requiring deep ML expertise that are found as a Service in AWS Cloud Portal:

Some of the AI Services which are pretrained:

• Amazon SageMaker JumpStart: Pre-built solutions for ML use cases.
• Amazon Rekognition: Image and video analysis.
• Amazon Polly: Text-to-speech.
• Amazon Transcribe: Automatic speech recognition.
• Amazon Translate: Language translation.
• Amazon Comprehend: Natural language processing (NLP).
• Amazon Lex: Build conversational interfaces (chatbots).
• Amazon Textract: Extract text and data from scanned documents.
• Amazon Forecast: Time series forecasting.
• Amazon Personalize: Personalized recommendations.
• Amazon Kendra: Intelligent search.
• AWS HealthImaging: Analyze and process medical imaging data.

AMAZON AI Services

ML Platforms and Tools

These services enable data scientists and developers to build, train, and deploy ML models:

• Amazon SageMaker:
• Comprehensive platform for building, training, and deploying ML models.
• Includes features like SageMaker Studio, Data Wrangler, and Autopilot.
• AWS Deep Learning AMIs: Pre-configured EC2 instances for deep learning frameworks.
• AWS Deep Learning Containers: Docker images for TensorFlow, PyTorch, etc.
• AWS Elastic Inference: Attach GPU inference acceleration to EC2 and SageMaker instances.
• AWS Neuron SDK: Optimize deep learning for AWS Inferentia and Trainium chips.

AWS ML Services

Infrastructure for ML

These services provide scalable infrastructure for ML workloads:

• Amazon EC2 Instances for ML:
• GPU instances (e.g., P4, G5) for ML training and inference.
• Inferentia and Trainium instances for cost-effective ML acceleration.
• AWS Lambda: Deploy lightweight ML inference models as serverless functions.
• Amazon Elastic Kubernetes Service (EKS): Run Kubernetes-based ML workflows.
• Amazon Elastic Container Service (ECS): Containerize ML workloads.
• AWS Outposts: Extend ML services to on-premises environments.

Data Services for ML

These services assist with preparing, storing, and managing ML datasets:

• AWS Glue: Data preparation and ETL for ML workflows.
• Amazon Redshift ML: Build and train ML models directly in Redshift.
• Amazon QuickSight Q: Business intelligence with ML-powered natural language queries.
• Amazon DataZone: Organize, discover, and govern ML data.
• AWS Lake Formation: Build a secure data lake for ML.
• Amazon Kinesis: Real-time data streaming for ML applications

Robotics and Edge ML

For deploying ML models at the edge or in robotics:

• AWS IoT Greengrass: Run ML inference at the edge.
• Amazon Monitron: Industrial equipment monitoring using ML.
• AWS RoboMaker: Develop, test, and deploy intelligent robotics.

Specialized ML Services

For domain-specific applications:

• Amazon Fraud Detector: Detect online fraud using ML.
• Amazon Lookout for Equipment: Predict industrial equipment failures.
• Amazon Lookout for Metrics: Detect anomalies in business metrics.
• Amazon Lookout for Vision: Detect visual defects in images.
• AWS Panorama: Computer vision at the edge.