AI for developers: Making your application smarter with Azure AI Services.
Slide 2
Originally from Mexico.
Tech Lead at Geneca.
Spend time with family, movies, videogames, football.
@thesoccerdev drkclw samueljgomez
Slide 3
Agenda • AI implementation options. • Why use Azure AI Services. • Azure AI services APIs. • Demo.
Slide 4
AI / ML
Slide 5
AI Implementation options.
Prebuilt models
Build model
Slide 6
Building your own model Collect and Identify data
prepare data 2
1
Train model 3
Deploy model Test model 4
5
Slide 7
Why use AI Services • APIs for multiple scenarios. • Easy to integrate with available SDKs: • • • • •
C# Go Java Javascript Python
• Free tier for multiple services. • Customizable.
Slide 8
API categories
Speech
Language
Vision
Decision
Slide 9
API categories
Translator
Slide 10
Speech
Slide 11
Speech API Improve customer experience Speech to text
Text to speech
Speech translation
Speaker recognition
Slide 12
Language
Slide 13
Language API Understand conversations and text Entity recognition
Sentiment analysis
Question answering
Conversational language understanding
Summarization
Slide 14
Language API Understand conversations and text Text analytics for health
Slide 15
Vision
Slide 16
Vision API Identify and analyze content
Computer Vision
Custom Vision
Face API
Slide 17
Decision
Slide 18
Decision API Smarter decisions
Anomaly Detector
Content Safety
Personalizer
Slide 19
Translator
Slide 20
Translator API Translate text
Text translation
Document translation
Custom translator
Slide 21
Other APIs
Slide 22
Other APIs
Document Intelligence
Immersive reader
Metrics advisor
Video indexer
Slide 23
Other APIs
Cognitive search
Bot service
Slide 24
Data privacy and security. • Authentication. • Data encrypted at rest and in transit. • Limited access features. • Data storage. • Data not stored. • Temporary
Slide 25
DEMO
Slide 26
What will we cover? • Creating a resource. • Testing APIs. • API usage examples.
• Vision. • Speech to text. • Language understanding.
• Custom model example.