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All technological notes.

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AWS - ML, AI, And Big Data

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• AWS - ML, AI, And Big Data
  • Terminology
  • Amazon QuickSight - BI
  • Amazon Rekognition - object recognition
  • Amazon Textract - Scan >> text
  • Amazon Transcribe - speech-to-text
  • Amazon Polly - text-to-speech
  • Amazon Translate - translation
  • Amazon Lex - chatbots
  • Amazon Connect - virtual contact center
  • Amazon Comprehend - NLP, understand text
  • Amazon SageMaker - ML Modeling
  • Amazon Forecast - predict for planning
  • Amazon Kendra - document search engine
  • Amazon Personalize - real-time personalized recommendations
  • Summary

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Terminology

• Artificial Intelligence (AI)

  • machines that perform jobs that mimic human behavior.

• Machine Learning (ML)

  • machines that get better at a task without explicit programming.

• Deep Learning (DL)

  • machines that have an artificial neural network inspired by the human brain to solve complex problems.

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• Big Data

  • a term used to describe massive volumes of structured/unstructured data that is so large it is difficult to move and process using traditional database and software techniques.

• Kafka

  • an open-source platform for building real-time streaming data pipelines and applications.

• Data Lake

  • a storage repository that holds a vast amount of raw data in its native format until it is needed.

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Amazon QuickSight - BI

• Amazon QuickSight
  • a Business Intelligence (BI) Dashboard that allows to ingest data from various AWS storage or database services to quickly visualize business data with minimal programming or data formula knowledge.

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Amazon Rekognition - object recognition

• 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)

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Amazon Textract - Scan » text

• 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)

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Amazon Transcribe - speech-to-text

• 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

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Amazon Polly - text-to-speech

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

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Amazon Translate - translation

• 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.

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Amazon Lex - chatbots

• 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

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Amazon Connect - virtual contact center

• 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

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Amazon Comprehend - NLP, understand text

• 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

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Amazon SageMaker - ML Modeling

• Amazon SageMaker

  • a fully managed service to build, train, and deploy machine learning model at scale.
    • Apache MXNet on AWS, open-source deep learning framework.
    • TensorFlow on AWS, open-source machine intelligence library.
    • PyTorch on AWS, open-source machine learning framework.
• 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).

• Amazon SageMaker Ground Truth

  • a data-labeling service.
  • label a dataset that will be used to train machine learning models.

• Amazon Augmented AI

  • human-intervention review service.
  • When SageMaker’s uses machine learning to make a prediction that is not confident it has the right answer queue up the predication for human review.
• label -> build -> Train and Tune -> ML model -> Apply model -> Prediction

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Amazon Forecast - predict for planning

• 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, …

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Amazon Kendra - document search engine

• 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, …)

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Amazon Personalize - real-time personalized recommendations

• 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…

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Summary

• Rekognition
  • : face detection, labeling, celebrity recognition

• Textract:

  • detect text and data in documents
• 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

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