This blog is a part of my journey “Embarking on the AWS Solution Architect Associate SAA-CO3 Certification Journey”

AWS offers a wide range of machine learning (ML) services designed to help developers and data scientists build, train, and deploy machine learning models quickly and easily. These services cover various aspects of the machine learning lifecycle, from data preparation to model deployment. Here are some of the key machine learning services offered by AWS:

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
  • Pathing (ex: for sports game analysis)
• Detect content that is inappropriate, unwanted, or offensive (image and videos)
• Used in social media, broadcast media, advertising, and e-commerce situations to create a safer user experience
• Set a Minimum Confidence Threshold for items that will be flagged
• Flag sensitive content for manual review in Amazon Augmented AI (A2I)
• Help comply with regulations

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
• Automatically remove Personally Identifiable Information (PII) using Redaction
• Supports Automatic Language Identification for multi-lingual audio
• 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
• Customize the pronunciation of words with Pronunciation lexicons
  • Stylized words: St3ph4ne => “Stephane”
  • Acronyms:AWS=>“AmazonWebServices”
• Upload the lexicons and use them in the SynthesizeSpeech operation
• Generate speech from plain text or from documents marked up with Speech Synthesis Markup Language (SSML) – enables more customization
  • emphasizing specific words or phrases
  • using phonetic pronunciation
  • including breathing sounds, whispering
  • using the Newscaster speaking style

Amazon Translate

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• 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 chatbots, call center bots
• Amazon Connect:
  • Receive calls, create contact flows, cloud-based vir tual 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 Comprehend Medical

• Amazon Comprehend Medical detects and returns useful information in unstructured clinical text:
  • Physician’s notes
  • Discharge summaries
  • Test results
    
  • Case notes
• Uses NLP to detect Protected Health Information (PHI) – DetectPHI API
• Store your documents in Amazon S3, analyze real-time data with Kinesis Data Firehose, or use Amazon Transcribe to transcribe patient narratives into text that can be analyzed by Amazon Comprehend Medical

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

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, …)

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)

AWS Machine Learning – Summary

• Rekognition: face detection, labeling, celebrity recognition • Transcribe: audio to text (ex: subtitles)
• Polly: text to audio
• Translate: translations
• Lex: build conversational bots – chatbots
• 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