Machine Learning Flashcards
- 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
Amazon Rekognition
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)
Amazon Rekognition
- 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 Rekognition – Content Moderation
- 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
Amazon Transcribe
Use cases:
* transcribe customer service calls
* automate closed captioning and subtitling
* generate metadata for media assets to create a fully searchable archive
Amazon Transcribe
- Turn text into lifelike speech using deep learning
- Allowing you to create applications that talk
Amazon Polly
Amazon Polly - Customize the pronunciation of words
Pronunciation lexicons
Amazon Polly - Upload the lexicons and use them in the __________ operation
SynthesizeSpeech
Amazon Polly - Generate speech from plain text or from documents marked up with _________________ – enables more customization
* emphasizing specific words or phrases
* using phonetic pronunciation
* including breathing sounds, whispering
* using the Newscaster speaking style
Speech Synthesis Markup Language (SSML)
- 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 Translate
(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 Lex
- 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 Connect
- 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 it will uncover
Amazon Comprehend
- 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 Comprehend Medical
- 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 SageMaker
- 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 Forecast
- 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 Kendra
- 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 Personalize
- 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)
Amazon Textract
face detection, labeling, celebrity recognition
Rekognition
audio to text (ex: subtitles)
Transcribe
text to audio
Polly
translations
Translate
build conversational bots – chatbots
Lex
cloud contact center
Connect
natural language processing
Comprehend
machine learning for every developer and data scientist
SageMaker
build highly accurate forecasts
Forecast
ML-powered search engine
Kendra
real-time personalized recommendations
Personalize
