SAA - C03 Certification: Machine Learning
I am a dedicated software engineer with a deep passion for security and a commitment to developing robust and scalable solutions. With over three years of hands-on experience in the .NET ecosystem, I have built, maintained, and optimized various software applications, demonstrating my ability to adapt to diverse project needs. In addition to my expertise in .NET, I have six months of specialized experience working with Spring Boot and ReactJS, further broadening my skill set to include full-stack development and modern web technologies. My professional journey includes deploying small to medium-sized systems to cloud platforms and on-premises environments, where I have ensured reliability, scalability, and efficient resource utilization. This combination of skills and experience reflects my versatility and commitment to staying at the forefront of the ever-evolving tech landscape.
Amazon Rekognition
Find objects, text, people, and 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 them to celebrities
Use cases:
Labeling
Content Moderation
Text Detection
Face Detection and Analysis
Face Search and Verification
Celebrity Regonnition
Pathing
Content Moderation
Detect content that is inappropriate, unwanted, or offensive (images 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
Amazon Transcribe
Automatically convert speech to text
Use cases:
transcribe customer service calls
automate closed captioning and subtitling
generate metadata for media assets
Amazon Polly
Turn text into lifelike speech using deep learning
Allowing the creation application to talk
Lexicon & SSML
Customize the pronunciation of words with Pronunciation Lexicons
Stylized words: St3ph4ne => “Stephane”
Acronyms: AWS => “Amazon Web Services”
Upload the lexicons and use them in SynthesizeSpeech
Generate speech from plain text or documents marked up with Speech Synthesis Markup Language (SSML)
Amazon Lex & Connect
Amazon Lex: (like Siri)
Automatic Speech Recognition to convert speech to text
Natural Language Understanding to recognize the intent of text, callers
Help build chatbots, call center bots
Amazon Connect:
Receive calls, create contact flows, and 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 NLP
Fully managed and serverless service
Uses ML to find insights and relationships in text
Use cases:
analyze customer interactions
create and group articles by topics
Comprehend Medical
Detects and returns useful information in unstructured clinical text: Physician’s notes, Discharge summaries, and Test results,…
Use NLP to detect Protected Health Information
SageMaker
Fully managed service to build LM models
Typically difficult to do all the processes in one place + provision services
Amazon Forecast
Fully managed service that uses ML to deliver highly accurate forecasts
Example: predict the future sales of a raincoat
Use cases: Product Demand Planning, Financial Planning,…
Amazon Kendra
Fully managed document search service powered by ML
Extract answers from a document
Amazon Personalize
Fully managed ML service to build apps with real-time personalized recommendations
Use cases: retail stores, media, and entertainment,…
Amazon Textract
- Automatically extracts text, handwriting, and data from any scanned documents using AL and ML
Summary
Rekognition: face detection, labeling
Transcribe: audio to text
Polly: text to audio
Translate: translations
Lex: build conversational bots- chatbots
Connect: cloud contact center
Comprehend: NLP
SageMaker: build ML model
Forecast: build highly accurate forecasts
Kendra: ML-powered search engine
Personalize: real-time personalized recommendations
Textract: detect text and data in documents