Machine Learning
AWS ML and generative AI services — SageMaker, Bedrock, Rekognition, Comprehend, and more. From foundation models and retrieval-augmented generation to custom training and inference.
Amazon Comprehend Medical: How It Works & When to Use It
Amazon Comprehend Medical is a HIPAA-eligible NLP service extracting medical info from text. Understand complex medical terms in notes & records. Learn when to choose it.
SageMaker Ground Truth: Build ML Datasets Easily
Amazon SageMaker Ground Truth is a managed data labeling service for ML. Streamline training data creation for supervised learning. Learn how it works.
Amazon CodeWhisperer: AI Coding Companion for Productivity
Amazon CodeWhisperer is an ML-powered AI coding companion that generates real-time code recommendations. Improve developer productivity. Learn how it works and when to use it.
Amazon Augmented AI (A2I): How It Works & Use Cases
Amazon Augmented AI (A2I) simplifies human review workflows for ML predictions. Integrate human judgment to improve accuracy. Learn when to use it.
Bedrock Guardrails: Secure Your Generative AI Apps
Bedrock Guardrails implements safeguards for generative AI apps, aligning interactions with company policies. Prevent harmful content. Learn how to use it.
Bedrock Agents: Build Apps for Complex Tasks
Amazon Bedrock Agents lets developers build apps that execute multi-step tasks using FMs. Understand requests, call APIs, and access data. Learn when to use it.
SageMaker JumpStart: Accelerate ML with Pre-trained Models
Amazon SageMaker JumpStart is an ML hub for one-click access to pre-trained models & solutions. Accelerate your ML journey. Learn how to deploy & fine-tune models.
SageMaker Pipelines: Automate ML Workflows
Amazon SageMaker Pipelines is a serverless service for building, automating, and managing end-to-end ML workflows. Streamline your CI/CD for ML. Learn when to use it.
SageMaker Endpoint: Deploy ML Models & Get Predictions
A SageMaker Endpoint deploys ML models for predictions via HTTPS API. Learn how it works, its benefits, and when to use it for real-time inference.
SageMaker Studio: Your ML IDE for Productivity
Amazon SageMaker Studio is a web-based IDE for ML, unifying all development steps. Boost data science team productivity. Learn when to use it.
Amazon Q Business: How It Works & When to Use It
Amazon Q Business is a generative AI assistant for enterprises. Connects to your data to answer questions, summarize info, and automate tasks. Learn its use cases.
Amazon Kendra: Intelligent Search for Your Data
Amazon Kendra is an ML-powered enterprise search service that finds answers in your data. Learn its definition, use cases, and when to implement it.
Amazon Forecast: What It Is & When to Use It
Amazon Forecast is a managed time-series forecasting service using ML. Learn about its features, use cases, and current status as AWS recommends SageMaker Canvas.
Amazon Personalize: How It Works & When to Use It
Amazon Personalize is a fully managed ML service for building recommendation tech apps. Deliver personalized experiences to boost engagement. Learn when to use it.
Amazon Textract: Extract Text & Data from Docs
Amazon Textract extracts text, handwriting, and data from documents. Automate workflows by identifying form fields and table data. Learn when to use it.
Amazon Lex: Build Conversational AI with Voice & Text
Amazon Lex is an AI service for building voice & text conversational interfaces. Leverage Alexa tech for chatbots & voice assistants. Learn when to use it.
Amazon Translate: Fast, High-Quality Neural Machine Translation
Amazon Translate is a neural machine translation service for fast, high-quality, affordable language translation. Translate text & documents easily. Learn when to use it.
Amazon Transcribe: Convert Speech to Text Easily
Amazon Transcribe is an AI service that converts speech to text using ASR. Add speech-to-text to apps & extract info from audio/video. Learn when to use it.
Amazon Polly: Natural Text-to-Speech for Apps
Amazon Polly is a cloud-based TTS service converting text to lifelike speech. Voice-enable your applications. Learn how it works and when to use it.
Amazon Comprehend: NLP Service for Text Analysis
Amazon Comprehend is an NLP service using ML to analyze text, uncovering insights like sentiment and entities. Learn its uses and benefits.
Amazon SageMaker: Managed ML Lifecycle Platform on AWS
Amazon SageMaker is AWS's end-to-end ML platform. Learn Studio IDE, training jobs, hyperparameter tuning, real-time/serverless/async endpoints, Pipelines, Feature Store, and MLOps.
Amazon Rekognition: Image and Video Analysis on AWS
Amazon Rekognition is AWS's managed computer vision API. Learn Labels, Faces, Text, Moderation, Custom Labels, video analysis, celebrity detection, and per-image/minute pricing.
Amazon Q Developer: AI Coding Assistant on AWS Explained
Amazon Q Developer is AWS's AI coding assistant (formerly CodeWhisperer). Learn inline suggestions, chat, /dev, /review, /test agents, IDE plugins, security scans, and pricing tiers.
Amazon Bedrock: Managed Foundation Model API Explained
Amazon Bedrock is AWS's managed foundation model API. Learn Claude, Titan, Nova, Llama, Mistral, Cohere models, Converse API, Knowledge Bases, Agents, Guardrails, and token pricing.
Bedrock Knowledge Bases: Managed RAG on AWS Explained
Amazon Bedrock Knowledge Bases is AWS's managed RAG service. Learn ingestion from S3/SharePoint/Confluence, chunking, vector stores, RetrieveAndGenerate API, and pricing.