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
