AWS Cloud Practitioner Certification

Machine Learning

Index

1. Amazon Reckognition
2. Amazon Transcribe
3. Amazon Polly
4. Amazon Translate
5. Amazon Lex & Connect
6. Amazon Comprehend
7. Amazon SageMaker
8. Amazon ForeCast
9. Amazon Kendra
10. Amazon Personalise

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 game 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
• • 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 systems 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 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 Forecast

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 Kendra (abbr. like ELK i.e document(text/pdf/word etc.) search service)

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 Personalize

• Fully managed ML-service to build apps with real-time personalised 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

1. Amazon Rekognition – Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content
2. AWS DeepLens – AWS DeepLens helps put machine learning in the hands of developers, literally, with a fully programmable video camera, tutorials, code, and pre-trained models designed to expand deep learning skills
3. Amazon Sage Maker – ML capability to developer/scrients to build ML model e. score predicting
4. Amazon Translate – Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation
5. Amazon Augmented AI – Amazon Augmented AI (Amazon A2I) makes it easy to build the workflows required for human review of ML predictions