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Azure Cognitive Services:
Mood Analyzer
Hello!
I’m Sherry List
Azure Developer Technical Lead, Microsoft
You can find me at @SherrryLst
AI, ML, DL, ANN?
@Sherrrylst
Artificial Intelligence
AI is the simulation of human intelligence
processes by machines. These
processes include, reasoning,
remembering, learning and self-
correction.
@Sherrrylst
Machine Learning
@Sherrrylst
Machine learning is a field of computer
science that gives computers the ability
to learn without being explicitly
programmed.
Arthur Samuel, 1959
Machine learning techniques
@Sherrrylst
• Artificial Neural Networks
• Deep Learning
• Bayesian Networks
• Clustering
Artificial Intelligence (AI)
The bigger picture
Machine
Learning
Artificial Neural Networks
Deep Learning
Bayesian Networks
Clustering
@Sherrrylst
Machine
Learning 101
@Sherrrylst
Machine Learning 101
@Sherrrylst
Data
@Sherrrylst
Data
Patterns
Machine Learning 101
@Sherrrylst
Data
Patterns
Algorithm
(Deep learning, clustering, …)
Machine Learning 101
@Sherrrylst
Data
Patterns
Algorithm
(Deep learning, clustering, …)
Find patterns
Machine Learning 101
@Sherrrylst
Data
Patterns
Model
Algorithm
(Deep learning, clustering, …)
Find patterns
Machine Learning 101
@Sherrrylst
Data
Patterns
Model
Algorithm
(Deep learning, clustering, …)
Find patterns Recognizes patterns
Machine Learning 101
@Sherrrylst
Data
Patterns
Model
Algorithm
(Deep learning, clustering, …)
Find patterns Recognizes patterns
Training
Machine Learning 101
@Sherrrylst
Data
Patterns
Model
Algorithm
(Deep learning, clustering, …)
Find patterns Recognizes patterns Application
Training
Machine Learning 101
@Sherrrylst
Data
Patterns
Model
Algorithm
(Deep learning, clustering, …)
Find patterns Recognizes patterns Application
Challenges
Data preparation
@Sherrrylst
Data
Patterns
Model
Algorithm
(Deep learning, clustering, …)
Find patterns Recognizes patterns Application
Challenges
Data preparation Create and test algorithms
@Sherrrylst
Algorithm
(Deep learning, clustering, …)
Find patterns
Challenges
Create and test algorithms
Chihuahua or muffin?
@Sherrrylst
Data
Patterns
Model
Algorithm
(Deep learning, clustering, …)
Find patterns Recognizes patterns Application
Challenges
Data preparation Create and test algorithms Expose the model to app
Is there a better
way?
@Sherrrylst
Azure
Cognitive
Services
@Sherrrylst
@Sherrrylst
Application
The easier way
Azure Cognitive
Services
REST API
Azure Cognitive Services === machine-learning-as-a-service
@Sherrrylst
@Sherrrylst
Application
The easier way
Azure Cognitive
Services
REST API
Azure Cognitive Services
Decision Speech Language Search Vision
@Sherrrylst
Decision
(Cognitive Services)
@Sherrrylst
@Sherrrylst
• Content Moderator
Cognitive Services - Decision
@Sherrrylst
• Content Moderator
• Anomaly Detector (Preview)
Cognitive Services - Decision
@Sherrrylst
• Content Moderator
• Anomaly Detector (Preview)
• Personalizer(Preview)
Cognitive Services - Decision
Speech
(Cognitive Services)
@Sherrrylst
• Speech Services
• Speech to Text
• Text to Speech
• Business Scenario (Call center)
@Sherrrylst
Cognitive Services - Speech
• Speech Services
• Speaker recognition (Preview)
@Sherrrylst
Cognitive Services - Speech
@Sherrrylst
Language
(Cognitive Services)
• Language Understanding
@Sherrrylst
Cognitive Services - Language
• Language Understanding
• Bing Spell Check
@Sherrrylst
Cognitive Services - Language
• Language Understanding
• Bing Spell Check
• Translator Text
@Sherrrylst
Cognitive Services - Language
• Language Understanding
• Bing Spell Check
• Translator Text
• Text Analytics
@Sherrrylst
Cognitive Services - Language
• Language Understanding
• Bing Spell Check
• Translator Text
• Text Analytics
• QnA Maker
@Sherrrylst
Cognitive Services - Language
@Sherrrylst
Search
(Cognitive Services)
Cognitive Services - Search
@Sherrrylst
• Bing Custom Search
• Bing Web Search
• Bing Video Search
• Bing Image Search
• Bing Local Business Search (Preview)
• Bing Visual Search
• Bing Entity Search
• Bing News Search
• Bing Auto Suggest
@Sherrrylst
Vision
(Cognitive Services)
• Computer vision
@Sherrrylst
Cognitive Services - Vision
• Computer vision
• Video Indexer
@Sherrrylst
Cognitive Services - Vision
• Computer vision
• Video Indexer
• Face
@Sherrrylst
Cognitive Services - Vision
• Computer vision
• Video Indexer
• Face
• Custom Vision
@Sherrrylst
Cognitive Services - Vision
• Computer vision
• Video Indexer
• Face
• Custom Vision
• Ink Recognizer (Preview)
@Sherrrylst
Cognitive Services - Vision
• Computer vision
• Video Indexer
• Face
• Custom Vision
• Ink Recognizer (Preview)
• Form Recognizer (Preview)
@Sherrrylst
Cognitive Services - Vision
How to use it?
@Sherrrylst
How to use Cognitive Services?
1. Create service in Azure Portal
(https://portal.azure.com/)
@Sherrrylst
How to use Cognitive Services?
1. Create service in Azure Portal
(https://portal.azure.com/)
2. Customize and train model in the
portal (Optional)
@Sherrrylst
How to use Cognitive Services?
1. Create service in Azure Portal
(https://portal.azure.com/)
2. Customize and train model in the
portal (Optional)
3. Call the REST API from your app
@Sherrrylst
How to use Cognitive Services?
1. Create service in Azure Portal
(https://portal.azure.com/)
2. Customize and train model in the
portal (Optional)
3. Call the REST API from your app
4. Parse the JSON response
@Sherrrylst
Let’s do it!
@Sherrrylst
Create a Cognitive Services account in the
Azure portal
@Sherrrylst
@Sherrrylst
Cognitive Services account - Face
Face API
@Sherrrylst
Cognitive Services account
@Sherrrylst
• URL : {Endpoint}/face/v1.0/detect
• URI Parameters
• Location
• returnFaceLandmarks (Boolean)
• returnFaceAttributes
• age,gender,smile,glasses,emotion,facialHair
• Headers
• Content-Type: application/octet-stream | application/json
• Ocp-Apim-Subscription-Key
Face API - Detect
Face API Documentation
@Sherrrylst
Face API - Detect
Face API Documentation
<code />
@Sherrrylst Source code
{N} Playground
@Sherrrylst
@Sherrrylst
Face API – Mood Analyzer
async runFaceDetect() {
this.dataSource = [];
const imageAsset = await takePicture(
{
width: 300,
height: 500,
keepAspectRatio: true,
saveToGallery: false
});
const filePath = await this.getFilePath(imageAsset);
const imageFile = File.fromPath(filePath);
this.pictureFromCamera = imageAsset;
this.result = await this.sendRequest(imageFile);
this.dataSource = getEmotionData(this.result);
}
Source code
@Sherrrylst
Face API – Posting data (Part 1)
sendRequest(file: File): Promise<any> {
return new Promise((resolve, reject) => {
const ses = session('image-upload');
const request = {
url: this.faceUrl,
method: 'POST',
headers: {
'Content-Type': 'application/octet-stream',
'Ocp-Apim-Subscription-Key': '7d30f6357121430e91b3f8439b8205c6',
},
description: 'Uploading ' + file.name
};
const task = ses.uploadFile(file.path, request);
...
});
}
Source code
@Sherrrylst
Face API – Posting data (Part 2)
sendRequest(file: File): Promise<any> {
return new Promise((resolve, reject) => {
...
task.on('error',
e => reject('error ' + e.responseCode + ' code.')
)
task.on('responded',
e => {
const data = JSON.parse(e.data);
return resolve(data);
}
);
});
}
Source code
@Sherrrylst
Face API – Posting data
async runFaceDetect() {
this.dataSource = [];
const imageAsset = await takePicture(
{
width: 300,
height: 500,
keepAspectRatio: true,
saveToGallery: false
});
const filePath = await this.getFilePath(imageAsset);
const imageFile = File.fromPath(filePath);
this.pictureFromCamera = imageAsset;
this.result = await this.sendRequest(imageFile);
this.dataSource = getEmotionData(this.result);
}
Source code
@Sherrrylst
Demo
Source code
Scan the code
@Sherrrylst
AI.lab@Sherrrylst
Azure Cognitive Services re-cap
@Sherrrylst
• Easy to use (REST API)
• Easy to provision
• Provide pre-trained models
• Possibility to use custom data
• Free training resources
• Detailed documentation
• Create account for free
@sebawita
Thank you!
@Sherrrylst
Thank you!
https://aka.ms/dot-net-madrid
Sample code
@Sherrrylst
https://aka.ms/AA5bt1y
Resources
• Microsoft Azure Cognitive Services: The Big Picture
• The Mojifier (MS Learn)
• The Mojifier (Github)
• Azure Cognitive Services API - I need your clothes, boots and your motorcycle
• Add conversational intelligence to your apps by using LUIS (MS Learn)
• Discover sentiment in text with the Text Analytics API (MS Learn)
• Create Intelligent Bots with the Azure Bot Service (MS Learn)
• Getting started with Azure Cognitive Services

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Azure Cognitive Services: Mood Analyzer

Editor's Notes

  1. Devices that can remember, learn, understand and recognize things
  2. ML is all about the ability to learn. Applications that can learn without hardcoding different scenarios.
  3. ML is used in many applications to detect the patterns, Is this a cat or a dog. In order to detect these patterns, you need to use different techniques. ANN: Mimics the way that human brain works DL: Learn from many layers of analysis where each layer has the input from the previous layer
  4. AI is the overall concept to make computers intelligent
  5. You use Machine learning to analyze the data
  6. You use Machine learning to analyze the data
  7. This data contains patterns. How a cat looks like or How a dog looks like
  8. You analyze this data with Machine learning algorithm
  9. To find patterns
  10. With those we create a Model, which is the outcome of this process
  11. Model is the thing to recognizes the patterns
  12. This process is also called training a model
  13. Now application can enter data to see if it can recognize a pattern.
  14. Preparing a set of data with diversity and covers the edge cases
  15. Creating the algorithms and choosing the techniques can be challenging. Also testing the outcome and making sure we get the right result is also super challenging.
  16. This is not the most difficult way, but still it’s challenging to find a secure way with having the performance in mind
  17. Cognitive Services are RESTful APIs that exposes ML models to the outside world.
  18. Azure makes sure that the Cognitive Services are available, secured and perform well. We just need to communicate with the API
  19. You can use either available data or upload your own data
  20. - Detect potential offensive and unwanted images - Filter possible profanity and undesirable text - Moderate adult and racy content in videos - Use built-in review tool for best results
  21. Easily embed anomaly detection capabilities into your apps so users can quickly identify problems. - Monitor business health in real-time Conduct IoT-remote monitoring Leverage interactive data analytics Powerful inference engine looks at your time-series data set and automatically selects the right algorithm to maximize accuracy for your scenario. Automatic detection eliminates the need for labeled training data. Save time and stay focused on fixing problems as soon as they surface. Customizable settings let you fine-tune sensitivity to potential anomalies based on your business’s risk profile. Azure is the only major cloud provider that offers anomaly detection as an AI service.
  22. Create rich, personalized experiences for every user of your app Personalizer uses machine learning to discover what action to use in a context. Each learning loop has a model that is trained exclusively on data that you have sent to it via Rank and Reward calls.  Deliver rich personalized experiences in your apps Deploy anywhere, from the cloud to the edge Understand and easily manage the reinforcement learning loop
  23. Speech to Text  OR Text to Speech Speech Translation Business scenarios built on Speech Services Easily transcribe every call and optimize results through batch transcription and custom speech services enhanced for call center scenarios. Index call transcriptions for full-text search, or apply text analytics to detect sentiment, language, and key phrases for insights.
  24. Speech to Text  OR Text to Speech Speech Translation Business scenarios built on Speech Services Easily transcribe every call and optimize results through batch transcription and custom speech services enhanced for call center scenarios. Index call transcriptions for full-text search, or apply text analytics to detect sentiment, language, and key phrases for insights.
  25. Use your voice for verification. The API can be used to power applications with an intelligent verification tool. If the speaker claims to be of a certain identity use voice to verify this claim.
  26. Add natural language understanding to your apps Language Understanding integrates seamlessly with the Speech service for instant Speech to Intent processing, and with the Azure Bot Service, making it easy to create a sophisticated bot. Quickly build a custom language solution Powerful developer tools are combined with customizable pre-built apps and entity dictionaries, such as Calendar, Music, and Devices, so you can build and deploy a solution more quickly.  Enterprise-ready, available worldwide Enterprise-ready, available worldwide
  27. Add natural language understanding to your apps Language Understanding integrates seamlessly with the Speech service for instant Speech to Intent processing, and with the Azure Bot Service, making it easy to create a sophisticated bot. Quickly build a custom language solution Powerful developer tools are combined with customizable pre-built apps and entity dictionaries, such as Calendar, Music, and Devices, so you can build and deploy a solution more quickly.  Enterprise-ready, available worldwide Enterprise-ready, available worldwide
  28. Web-scale, multi-lingual spell checking Contextual spell checking
  29. Automatic language detection Automated text translation Customizable translation Add online and offline translation support into your Android app Transliterate into different alphabets
  30. Named Entity Recognition Key phrase extraction Text sentiment analysis
  31. Quickly extract questions and answers from your existing content
  32. Bing Custom Search -> Corporate search engine Bing Entity Search -> Detects pictures or persons to enrich the result
  33. Bing Custom Search -> Corporate search engine Bing Entity Search -> Detects pictures or persons to enrich the result
  34. Computer vision -> Analyze the data and return information like 4 storm troopers standing and sky is blue
  35. Computer vision -> Analyze the data and return information like 4 storm troopers standing and sky is blue
  36. Computer vision -> Analyze the data and return information like 4 storm troopers standing and sky is blue Video Indexer -> Analyze the video and extract the text and recognizes things that are in the video
  37. Face -> Detect faces and extract information about the face
  38. Custom Vision -> Upload different pictures of Princess Lea for training, so it can recognizes princess Lea
  39. Ink Recognizer -> Recognize handwriting created in digital ink, in 63 languages and locales, Identify common polygon shapes in digital ink, Enable productivity scenarios, such as converting handwriting to text and making inked content searchable.
  40. Form Recognizer -> Simple extraction Tailored results Extract text, key-value pairs, and tables from documents Customized to your forms, without manual labeling Deploy anywhere, from the cloud to the edge
  41. You can even create a guest account to try it without providing Credit card info and no data will be saved after trial is over (7 days)
  42. Posting image to Face API (Part 1)
  43. Posting image to Face API (Part 1)
  44. Posting image to Face API (Part 2)
  45. Posting image to Face API (Part 1)