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Machine Learning

Amazon Rekognition

  • Find objects, people, text, scenes in images and videos using ML
  • Facial analysis and facial search to do user verification, people counting
  • Create a database of “familiar faces” or compare against celebrities
  • Use cases:
  • Labeling
    • Content Moderation
    • Text Detection
    • Face Detection and Analysis (gender, age range, emotions…)
    • Face Search and Verification
    • Celebrity Recognition
  • https://aws.amazon.com/rekognition/

Amazon Transcribe

  • Automatically convert speech to text
  • Uses a deep learning process called automatic speech recognition (ASR) to convert speech to text quickly and accurately
  • Use cases:
    • transcribe customer service calls
    • automate closed captioning and subtitling
    • generate metadata for media assets to create a fully searchable archive

Amazon Polly

  • Turn text into lifelike speech using deep learning
  • Allowing you to create applications that talk

Amazon Translate

  • Natural and accurate language translation
  • Amazon Translate allows you to localize content - such as websites and applications - for international users, and to easily translate large volumes of text efficiently.

Amazon Lex & Connect

Amazon Lex: (same technology that powers Alexa)

  • Automatic Speech Recognition (ASR) to convert speech to text
  • Natural Language Understanding to recognize the intent of text, callers
  • Helps build chatbot, call center bots

Amazon Connect

  • Receive calls, create contact flows, cloud-based virtual contact center
  • Can integrate with other CRM systems or AWS
  • No upfront payments, 80% cheaper than traditional contact center solutions

Amazon Comprehend

  • For Natural Language Processing – NLP
  • Fully managed and serverless service
  • Uses machine learning to find insights and relationships in text
    • Language of the text
    • Extracts key phrases, places, people, brands, or events
    • Understands how positive or negative the text is
    • Analyzes text using tokenization and parts of speech
    • Automatically organizes a collection of text files by topic
  • Sample use cases:
    • analyze customer interactions (emails) to find what leads to a positive or negative experience
    • Create and groups articles by topics that Comprehend will uncover

Amazon SageMaker

  • Fully managed service for developers / data scientists to build ML models
  • Typically, difficult to do all the processes in one place + provision servers
  • Machine learning process (simplified): predicting your exam score

Amazon Forecast

  • Fully managed service that uses ML to deliver highly accurate forecasts
  • Example: predict the future sales of a raincoat
  • 50% more accurate than looking at the data itself
  • Reduce forecasting time from months to hours
  • Use cases: Product Demand Planning, Financial Planning, Resource Planning,etc..

Amazon Kendra

  • Fully managed document search service powered by Machine Learning
  • Extract answers from within a document (text, pdf, HTML, PowerPoint, MS Word, FAQs…)
  • Natural language search capabilities
  • Learn from user interactions/feedback to promote preferred results (Incremental Learning)
  • Ability to manually fine-tune search results (importance of data, freshness, custom,etc..)

Amazon Personalize

  • Fully managed ML-service to build apps with real-time personalized recommendations
  • Example: personalized product recommendations/re-ranking, customized direct marketing
    • Example: User bought gardening tools, provide recommendations on the next one to buy
  • Same technology used by Amazon.com
  • Integrates into existing websites, applications, SMS, email marketing systems, …
  • Implement in days, not months (you don’t need to build, train, and deploy ML solutions)
  • Use cases: retail stores, media and entertainment

Amazon Textract

  • Automatically extracts text, handwriting, and data from any scanned documents using AI and ML
  • Extract data from forms and tables
  • Read and process any type of document (PDFs, images, …)
  • Use cases:
    • Financial Services (e.g., invoices, financial reports)
    • Healthcare (e.g., medical records, insurance claims)
    • Public Sector (e.g., tax forms, ID documents, passports)

Summary

  • Rekognition: face detection, labeling, celebrity recognition
  • Transcribe: audio to text (ex: subtitles)
  • Polly: text to audio
  • Translate: translations
  • Lex: build conversational bots – chatbot
  • Connect: cloud contact center
  • Comprehend: natural language processing
  • SageMaker: machine learning for every developer and data scientist
  • Forecast: build highly accurate forecasts
  • Kendra: ML-powered search engine
  • Personalize: real-time personalized recommendations
  • Textract: detect text and data in documents

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