Machine Learning

Question 1

Amazon Rekognition

Answer 1

• 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)

Question 2

Amazon Transcribe

Answer 2

• 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

Question 3

Amazon Polly

Answer 3

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

Question 4

Amazon Translate

Answer 4

• 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

Question 5

Amazon Lex & Connect

Answer 5

• 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 systems or AWS
  * No upfront payments, 80% cheaper than traditional contact center solutions

Question 6

Amazon Comprehend

Answer 6

• 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

Question 7

Amazon SageMaker

Answer 7

• Machine learning for every developer and data scientist
• 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

Question 8

Amazon Forecast

Answer 8

• 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, …

Question 9

Amazon Kendra

Answer 9

• 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, …)

Question 10

Amazon Personalize

Answer 10

• 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…

Question 11

Amazon Textract

Answer 11

• 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)