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KIKI RIZKI NOVIANDI
PT. Kwadran Lima Indonesia
http://www.Kwad5.com
Kiki.Rizki.Noviandi @KikiNoviandi krn@kwad5.com
https://mvp.microsoft.com/en-
us/PublicProfile/33869?fullName=Kiki%20Rizki%20Noviandi
Kiki Noviandi
@Microsoft-Jakarta | 24 – Nov - 2017
Microsoft
Cognitive
Services
Give your apps
a human side
Roll your own with REST APIs
Simple to add: just a few lines of
code required
Integrate into the language and
platform of your choice
Breadth of offerings helps you find the
right API for your app
Built by experts in their field from
Microsoft Research, Bing, and Azure
Machine Learning
Quality documentation, sample
code, and community support
Easy Flexible Tested
GET A
KEY
Scenarios
How do I use them?
Best practices for Devs
For ObjectiveC/Swift/iOS, Java/Android, C#/Windows, and Python (Jupyter notebook)
https://www.microsoft.com/cognitive-services/en-us/SDK-Sample?api=computer%20vision
Computer Vision API describes images in English only
Face API detects up to 64 human faces in one image
Facial detection: JPEG, PNG, GIF (first frame), and BMP supported, image file size of 1KB-4MB, detectable
face size 36x36-4096x4096 pixels, returned faces ordered by face rect size desc
FindSimilarFace has 2 modes: matchPerson (default, same person) and matchFace (similar faces)
FaceGroup API takes between 2-1000 candidate faces
Documentation: https://www.microsoft.com/cognitive-services/en-us/documentation
Computer Vision: 86 Categories
Data
Description, tags, clip art, line drawing, black & white, IsAdultContent/Score, IsRacy/Score, categories,
faces, dominant colors, accent color
https://www.microsoft.com/cognitive-services/en-us/computer-vision-api
Anger, contempt, disgust, fear, happiness, sadness, surprise, and neutral
https://www.microsoft.com/cognitive-services/en-us/emotion-api
Bounding box, 27 facial landmarks, age, gender, head pose, smile, facial hair, glasses
https://www.microsoft.com/cognitive-services/en-us/face-api
http://aifunclub.azurewebsites.net
http://captionbot.ai
http://microsoft.com/cognitive
Speech
http://text-analytics-demo.azurewebsites.net
Language understanding (LUIS)
Entities–DepartureCity, ArrivalCity, DepartureDate, ReturnDate
Intent–book a flight
Examples: “I want to go to Paris from Sept 25 to Sept 29, 2016”, “Book me a flight from DTW to CDG leaving
on 9/25/2016 and returning 9/28/2016”, etc.
See what real users are sending to your model, and map those utterances to intents (or create new intents
based on what your users are asking).
Language
Knowledge
Developer
Resources
Preview Pricing
https://www.microsoft.com/cognitive-services/en-us/pricing
Documentation
https://www.microsoft.com/cognitive-services/en-us/computer-vision-
api/documentation
Client SDKs and Samples
https://www.microsoft.com/cognitive-services/en-us/sdk-sample
Join Our Community
https://stackoverflow.com/questions/tagged/microsoft-cognitive
https://social.msdn.microsoft.com/forums/azure/en-US/home?forum=mlapi
https://cognitive.uservoice.com/
Why Microsoft
Cognitive Services?
Get started for free at
microsoft.com/cognitive
Immersion on Azure  - Data base and Cognitive Service at a glance

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