Merge pull request #12 from kananinirav/Nirav/machine-learning-services

[Modified / Added] Machine Learning Document

README.md

@@ -18,6 +18,7 @@
 - [Cloud Monitoring](sections/cloud_monitoring.md)
 - [VPC](sections/vpc.md)
 - [Security & Compliance](sections/Security-Compliance.md)
+- [Machine Learning](sections/machine-learning.md)
 
 ### Contributors
 

sections/machine-learning.md

@@ -0,0 +1,135 @@
+# Machine Learning
+
+- [Machine Learning](#machine-learning)
+  - [Amazon Rekognition](#amazon-rekognition)
+  - [Amazon Transcribe](#amazon-transcribe)
+  - [Amazon Polly](#amazon-polly)
+  - [Amazon Translate](#amazon-translate)
+  - [Amazon Lex & Connect](#amazon-lex--connect)
+    - [Amazon Lex: (same technology that powers Alexa)](#amazon-lex-same-technology-that-powers-alexa)
+    - [Amazon Connect](#amazon-connect)
+  - [Amazon Comprehend](#amazon-comprehend)
+  - [Amazon SageMaker](#amazon-sagemaker)
+  - [Amazon Forecast](#amazon-forecast)
+  - [Amazon Kendra](#amazon-kendra)
+  - [Amazon Personalize](#amazon-personalize)
+  - [Amazon Textract](#amazon-textract)
+  - [Summary](#summary)
+
+## 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
+- <https://aws.amazon.com/rekognition/>
+
+## 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 chatbot, 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,etc..
+
+## Amazon Kendra
+
+- 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,etc..)
+
+## Amazon Personalize
+
+- 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 Textract
+
+- 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)
+
+## Summary
+
+- Rekognition: face detection, labeling, celebrity recognition
+- Transcribe: audio to text (ex: subtitles)
+- Polly: text to audio
+- Translate: translations
+- Lex: build conversational bots – chatbot
+- 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
+- Textract: detect text and data in documents