Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
We can essentially train your machines to think like you would and make the decisions you would want them to make based on more data than you could process and sooner than you could process it.
Quickly and easily build, train, and deploy machine learning models with high-performance machine learning algorithms, broad framework support, and one-click training, tuning, and inference. Amazon SageMaker has a modular architecture so that you can use any or all of its capabilities in your existing machine learning workflows.
Amazon Polly uses advanced DL text-to-speech and speech-to-text technologies to synthesize speech that sounds like a human voice. This provides users with innovative ways to use applications and access information. The technology also has the potential to improve the quality of life for people who are unable to read text on a screen.
Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to fnd insights and relationships in text. You can use the Amazon Comprehend APIs in a wide range of applications including voice-of-customer analysis, intelligent document search, and content personalization for web applications.
Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easyfor developers to add speech-to-text capability to their applications. Amazon Transcribe can be used for lots of common applications, including the transcription of customer service calls and generating subtitles on audio and video content.
Amazon Translate uses neural machine translation to deliver fast, aﬀordable, high-quality language translation. Using machine le arning and deep learning models, Amazon Translate can deliver more accurate, natural-sounding translations than statistical and rule-based translation algorithms.