Develop CHATBOT with Microsoft Azure

Build and test a simple bot in web chat on Microsoft Azure, configuring forms, question and answer, and natural language processing. Deploy, connect to Facebook and Slack, and monitor analytics.

Learn to embed your web chat bot into a website by selecting a channel on the dashboard, copying the embedded code, and pasting it into your site, with security checks.

Learn how to deploy a web chat bot by integrating embedded code, handling secret keys securely, and connecting to channels such as email and Facebook from your website.

Create and configure a Facebook app, enable messenger, and link it to a new or existing Facebook page, using the dashboard to manage the app secret and messaging permissions.

Link your newly created Facebook page to a Facebook app, copy the base access token for future use, and configure messaging options and subscriptions with your app secret and callback.

Learn how to connect bot services with a Facebook app, configure Messenger settings, and navigate the approval process, privacy policy, and testing versus public publishing for a Facebook chatbot.

Learn how to deploy a Facebook chatbot, configure privacy policy settings, provide details, and test the chat as a developer before public launch.

Delete and disable Facebook chatbot channels, analyze usage with analytics, and manage cross-channel connections like Telegram, Line, Skype, and Microsoft Teams, then test with a service emulator.

Create a knowledge base by uploading data to Unit Maker, then extract and index content, and enable matching of user questions across channels via API or portal.

Create a knowledge base in QnA Maker by linking Microsoft Azure services, adding a subscription, uploading URLs or files, and choosing personalities such as professional, friendly, or comic.

Build and connect a knowledge base for a chatbot by crawling content from manuals and files, converting them into question-and-answer pairs, and testing the bot after training.

Test your trained knowledge base by asking questions and comparing answers, edit and tune responses, then publish the QnA bot with a postman link and monitor user feedback.

Explore Luis, a cloud-based language understanding API that uses custom ML to predict intents and extract entities from natural language for chatbots.

Create and test a LUIS app by designing intents and entities, configuring domains, training the model, and publishing, using a dashboard to build a home automation assistant.

Publish your LUIS app in Azure, configure the endpoint, location, and subscription key, generate the JSON for your utterances, then test and publish to production or staging.

Modify your LUIS app by editing intents, train after changes, publish and test updates, then add or edit entities like age and geography and create phrase lists.

Learn to build a LUIS sentiment analysis feature in an Azure chatbot, configure sentiment rules, train the app, and publish with app keys and a dashboard showing sentiment scores.