# Amazon Machine Learning Documentation Regardless of your experience, Amazon provides services that you can use to create machine learning solutions for a wide range of industries. ## Managed machine learning models - [Amazon Sagemaker](/sagemaker/): Use Amazon SageMaker to quickly build and train and deploy machine learning models, including Foundation Models for generative AI solutions. ## Automated data extraction and analysis - [Amazon Textract](/textract/): Amazon Textract enables you to add document text detection and analysis to your applications. - [Amazon Comprehend](/comprehend/): Amazon Comprehend uses natural language processing (NLP) to extract insights about the content of documents. - [Amazon A2I](/augmented-ai/): Amazon Augmented AI (Amazon A2I) enables you to build the workflows required for human review of ML predictions. ## Language AI - [Amazon Lex](/lex/): Amazon Lex is an AWS service for building conversational interfaces into applications using voice and text. - [Amazon Transcribe](/transcribe/): Amazon Transcribe provides transcription services for your audio files and audio streams. - [Amazon Polly](/polly/): Amazon Polly is a Text-to-Speech (TTS) cloud service that converts text into lifelike speech. ## Improve customer experience - [Amazon Kendra](/kendra/): Amazon Kendra is a search service, powered by machine learning, that enables users to search unstructured text using natural language. - [Amazon Personalize](/personalize/): Real-time personalization and recommendations, based on the same technology used at Amazon.com. - [Amazon Translate](/translate/): Amazon Translate is a neural machine translation service for translating text to and from English across a breadth of supported languages. ## Business metrics - [Amazon Forecast](/forecast/): Amazon Forecast is a fully managed deep learning service for time-series forecasting. - [Amazon Fraud Detector](/frauddetector/): Amazon Fraud Detector is a fully managed service that helps you detect suspicious online activities. - [Amazon Lookout for metrics](/lookout-for-metrics/): Amazon Lookout for Metrics is a machine learning service that helps you continuously find anomalies in business and operational data based on the same technology used by Amazon.com. ## Code and DevOps - [Amazon Devops Guru](/devops-guru/): Amazon DevOps Guru generates operational insights using machine learning to help you improve the performance of your operational applications. - [Amazon Code Guru Reviewer and Amazon Code Guru Profiler](/codeguru/): CodeGuru provides intelligent recommendations for improving application performance, efficiency, and code quality in your applications. ## Computer vision - [Amazon Rekognition](/rekognition/): Learn how to find objects, faces, in images and videos Amazon Rekognition. Use Amazon Custom Labels to create train your own computer vision model. ## Manufacturing and operations - [Amazon Lookout for Equipment](/lookout-for-equipment/): Amazon Lookout for Equipment uses industrial data from your equipment to detect potential failures so you can take action, such as performing maintenance before a breakdown, to avoid unplanned downtime. - [Amazon Lookout for Vision](/lookout-for-vision/): Amazon Lookout for Vision enables you to find visual defects in industrial products, accurately and at scale. - [Amazon Monitron](/monitron/): Amazon Monitron is an end-to-end system that detects abnormal behavior in industrial machinery enabling you to implement predictive maintenance and reduce unplanned downtime. - [AWS Panorama](/panorama/): Improve your operations with computer vision at the edge ## Infrastructure and frameworks - [AWS Deep Learning Containers](/deep-learning-containers/): AWS Deep Learning Containers (Deep Learning Containers) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. - [AWS Deep Learning AMIs](/dlami/): The AWS Deep Learning AMIs equip machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud at any scale. - [Apache MXNet on AWS](/mxnet/): Apache MXNet (MXNet) is an open source deep learning framework that allows you to define, train, and deploy deep neural networks on a wide array of platforms, from cloud infrastructure to mobile devices. - [Amazon Elastic Inference](/elastic-inference/): Amazon Elastic Inference is a service that allows you to attach low-cost GPU-powered acceleration to many Amazon machine instances in order to reduce the cost of running deep learning inference by up to 75%. ## Healthcare - [Amazon Comprehend Medical](/comprehend-medical/): Amazon Comprehend Medical detects and returns useful information in unstructured clinical text such as physicians notes, discharge summaries, test results, and case notes. - [AWS HealthLake](/healthlake/): AWS HealthLake is a Fast Healthcare Interoperability Resources (FHIR)-enabled patient Data Store. You can use AWS HealthLake to bring data from diverse sources into standard FHIR R4 format. - [AWS HealthOmics](/omics/): AWS HealthOmics stores, transforms, and analyze genomic and other biological data to generate health insights and advance scientific discoveries. ## Education and enablement - [AWS DeepComposer](/deepcomposer/): Get started with generative AI through the creation of a melody that transforms into a completely original song in seconds using AI. - [AWS DeepLens](/deeplens/): Learn the basics of deep learning through computer vision projects, tutorials, and real world, hands-on exploration. - [AWS DeepRacer](/deepracer/): Get hands-on with machine learning through a 3D racing simulator, fully autonomous 1/18th scale car, and global racing league. ## No longer supported documentation We are no longer updating the Amazon Machine Learning service or accepting new users for it. This documentation is available for existing users, but we are no longer updating it. - [Amazon Machine Learning Developer Guide](/machine-learning/latest/dg/): Provides a conceptual overview of Amazon Machine Learning and includes detailed instructions for using the service. - [Amazon Machine Learning API Reference](/machine-learning/latest/APIReference/): Describes all the API operations for Amazon Machine Learning in detail. Also provides sample requests and responses for supported web service protocols. --- ## Related Links - [AWS Glossary](http://docs.aws.amazon.com/general/latest/gr/glos-chap.html) - [Getting Started with AWS](https://aws.amazon.com/documentation/gettingstarted/) - [SDKs & Tools](https://aws.amazon.com/tools/) - [AWS General Reference](http://docs.aws.amazon.com/general/latest/gr/Welcome.html) - [AWS Training](https://aws.amazon.com/training/) - [AWS Case Studies](https://aws.amazon.com/solutions/case-studies/) - [AWS Whitepapers](https://aws.amazon.com/whitepapers/)