AWS - 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
  • Pathing (ex: for sports gam analysis)

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

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 chatbots, call center bots
• Amazon Connect:
  • Receive calls, create contact flows, cloud-based virtual contact center
  • Can integrate with other CRM system 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 scientist 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 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 users 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-tim 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 extract 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)