Azure Cognitive Services: Mood Analyzer
•Transferir como PPTX, PDF•
2 gostaram•486 visualizações
In this talk, we are going to have a quick overview of Azure cognitive services and then see how quickly you can build a {N} app which analyze your mood with the help of Face API
Recomendados
Mais conteúdo relacionado
Semelhante a Azure Cognitive Services: Mood Analyzer
Semelhante a Azure Cognitive Services: Mood Analyzer (20)
Último
Último (20)
Azure Cognitive Services: Mood Analyzer
- 1. Azure Cognitive Services: Mood Analyzer
- 2. Hello! I’m Sherry List Azure Developer Technical Lead, Microsoft You can find me at @SherrryLst
- 3. AI, ML, DL, ANN? @Sherrrylst
- 4. Artificial Intelligence AI is the simulation of human intelligence processes by machines. These processes include, reasoning, remembering, learning and self- correction. @Sherrrylst
- 5. 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
- 6. Machine learning techniques @Sherrrylst • Artificial Neural Networks • Deep Learning • Bayesian Networks • Clustering
- 7. Artificial Intelligence (AI) The bigger picture Machine Learning Artificial Neural Networks Deep Learning Bayesian Networks Clustering @Sherrrylst
- 11. @Sherrrylst Data Patterns Algorithm (Deep learning, clustering, …) Machine Learning 101
- 12. @Sherrrylst Data Patterns Algorithm (Deep learning, clustering, …) Find patterns Machine Learning 101
- 13. @Sherrrylst Data Patterns Model Algorithm (Deep learning, clustering, …) Find patterns Machine Learning 101
- 14. @Sherrrylst Data Patterns Model Algorithm (Deep learning, clustering, …) Find patterns Recognizes patterns Machine Learning 101
- 15. @Sherrrylst Data Patterns Model Algorithm (Deep learning, clustering, …) Find patterns Recognizes patterns Training Machine Learning 101
- 16. @Sherrrylst Data Patterns Model Algorithm (Deep learning, clustering, …) Find patterns Recognizes patterns Application Training Machine Learning 101
- 17. @Sherrrylst Data Patterns Model Algorithm (Deep learning, clustering, …) Find patterns Recognizes patterns Application Challenges Data preparation
- 18. @Sherrrylst Data Patterns Model Algorithm (Deep learning, clustering, …) Find patterns Recognizes patterns Application Challenges Data preparation Create and test algorithms
- 19. @Sherrrylst Algorithm (Deep learning, clustering, …) Find patterns Challenges Create and test algorithms Chihuahua or muffin?
- 20. @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
- 21. Is there a better way? @Sherrrylst
- 23. @Sherrrylst Application The easier way Azure Cognitive Services REST API
- 24. Azure Cognitive Services === machine-learning-as-a-service @Sherrrylst
- 25. @Sherrrylst Application The easier way Azure Cognitive Services REST API
- 26. Azure Cognitive Services Decision Speech Language Search Vision @Sherrrylst
- 28. @Sherrrylst • Content Moderator Cognitive Services - Decision
- 29. @Sherrrylst • Content Moderator • Anomaly Detector (Preview) Cognitive Services - Decision
- 30. @Sherrrylst • Content Moderator • Anomaly Detector (Preview) • Personalizer(Preview) Cognitive Services - Decision
- 32. • Speech Services • Speech to Text • Text to Speech • Business Scenario (Call center) @Sherrrylst Cognitive Services - Speech
- 33. • Speech Services • Speaker recognition (Preview) @Sherrrylst Cognitive Services - Speech
- 35. • Language Understanding @Sherrrylst Cognitive Services - Language
- 36. • Language Understanding • Bing Spell Check @Sherrrylst Cognitive Services - Language
- 37. • Language Understanding • Bing Spell Check • Translator Text @Sherrrylst Cognitive Services - Language
- 38. • Language Understanding • Bing Spell Check • Translator Text • Text Analytics @Sherrrylst Cognitive Services - Language
- 39. • Language Understanding • Bing Spell Check • Translator Text • Text Analytics • QnA Maker @Sherrrylst Cognitive Services - Language
- 41. 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
- 43. • Computer vision @Sherrrylst Cognitive Services - Vision
- 44. • Computer vision • Video Indexer @Sherrrylst Cognitive Services - Vision
- 45. • Computer vision • Video Indexer • Face @Sherrrylst Cognitive Services - Vision
- 46. • Computer vision • Video Indexer • Face • Custom Vision @Sherrrylst Cognitive Services - Vision
- 47. • Computer vision • Video Indexer • Face • Custom Vision • Ink Recognizer (Preview) @Sherrrylst Cognitive Services - Vision
- 48. • Computer vision • Video Indexer • Face • Custom Vision • Ink Recognizer (Preview) • Form Recognizer (Preview) @Sherrrylst Cognitive Services - Vision
- 49. How to use it? @Sherrrylst
- 50. How to use Cognitive Services? 1. Create service in Azure Portal (https://portal.azure.com/) @Sherrrylst
- 51. 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
- 52. 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
- 53. 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
- 55. Create a Cognitive Services account in the Azure portal @Sherrrylst
- 56. @Sherrrylst Cognitive Services account - Face Face API
- 58. @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
- 59. @Sherrrylst Face API - Detect Face API Documentation
- 60. <code /> @Sherrrylst Source code
- 62. @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
- 63. @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
- 64. @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
- 65. @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
- 69. 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
- 73. 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
Notas do Editor
- Devices that can remember, learn, understand and recognize things
- ML is all about the ability to learn. Applications that can learn without hardcoding different scenarios.
- 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
- AI is the overall concept to make computers intelligent
- You use Machine learning to analyze the data
- You use Machine learning to analyze the data
- This data contains patterns. How a cat looks like or How a dog looks like
- You analyze this data with Machine learning algorithm
- To find patterns
- With those we create a Model, which is the outcome of this process
- Model is the thing to recognizes the patterns
- This process is also called training a model
- Now application can enter data to see if it can recognize a pattern.
- Preparing a set of data with diversity and covers the edge cases
- 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.
- This is not the most difficult way, but still it’s challenging to find a secure way with having the performance in mind
- Cognitive Services are RESTful APIs that exposes ML models to the outside world.
- Azure makes sure that the Cognitive Services are available, secured and perform well. We just need to communicate with the API
- You can use either available data or upload your own data
- - 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
- 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.
- 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
- 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.
- 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.
- 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.
- 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
- 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
- Web-scale, multi-lingual spell checking Contextual spell checking
- Automatic language detection Automated text translation Customizable translation Add online and offline translation support into your Android app Transliterate into different alphabets
- Named Entity Recognition Key phrase extraction Text sentiment analysis
- Quickly extract questions and answers from your existing content
- Bing Custom Search -> Corporate search engine Bing Entity Search -> Detects pictures or persons to enrich the result
- Bing Custom Search -> Corporate search engine Bing Entity Search -> Detects pictures or persons to enrich the result
- Computer vision -> Analyze the data and return information like 4 storm troopers standing and sky is blue
- Computer vision -> Analyze the data and return information like 4 storm troopers standing and sky is blue
- 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
- Face -> Detect faces and extract information about the face
- Custom Vision -> Upload different pictures of Princess Lea for training, so it can recognizes princess Lea
- 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.
- 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
- 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)
- Posting image to Face API (Part 1)
- Posting image to Face API (Part 1)
- Posting image to Face API (Part 2)
- Posting image to Face API (Part 1)