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Machine Learning, Amazon Rekognition – Content Moderation, Amazon Kendra,…
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Amazon Kendra
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Extract answers from within a document (text, pdf, HTML, PowerPoint, MS Word, FAQs…)
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Ability to manually fine-tune search results (importance of data, freshness, custom, …)
Amazon Rekognition
Use case
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Face Detection and Analysis (gender, age range, emotions…)
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Find objects, people, text, scenes in images and videos using ML
Facial analysis and facial search to do user verification, people counting
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Amazon Transcribe
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Uses a deep learning process called automatic speech recognition (ASR) to convert speech to text quickly and accurately
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Amazon Personalize
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Integrates into existing websites, applications, SMS, email marketing systems, …
Implement in days, not months
Amazon Polly
Lexicon & SSML
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Generate speech from plain text or from documents marked up with Speech Synthesis Markup Language (SSML) – enables more customization
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Including breathing sounds, whispering
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Amazon Connect
Receive calls, create contact flows, cloud-based virtual contact center
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No upfront payments, 80% cheaper than traditional contact center solutions
Amazon Lex
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Natural Language Understanding to recognize the intent of text, callers
Helps build chatbots, call center bots
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Amazon SageMaker
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Typically, difficult to do all the processes in one place + provision servers
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Amazon Textract
Automatically extracts text, handwriting, and data from any scanned documents using AI and ML
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Read and process any type of document (PDFs, images, …)
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