What you will learn ?

• Real-world how IT projects are implemented
• Implement project using Slack , IBM Cloud Functions, Watson Visual Recognition,Watson Natural Language, Cloud
• Capture Requirements of the project using Use Case Modelling (Stakeholders, Personas, Main Scanario, Alternate, Negative, Edge Cases)
• Define Functional & Non-Functional Use Cases
• Create project design using UML Modelling
• Implement project coding using code respositories.
• How Google Analytics, Search Engine Optimization(SEO) are implemented.
• How UX Banners are created.
• Testing using unit tests(create & execute)
• Deployment of the project in cloud
• User Acceptance Testing - How client identify issues, how you fix issues
• Go Live of the project

Description

Rude behavior. Angry or inappropriate messages. Explicit images. All of these things are used daily in social media platforms. So how can you filter out these issues? By building a chatbot that monitors messages and images. You can use this monitoring in a chat room like Slack or a website that allows reviews, and it can remove explicit images or inappropriate text.

In this code pattern, you’ll create a chatbot that uses IBM® Cloud Functions and Watson™ services. The chatbot flow is enhanced by using Watson Visual Recognition and Watson Natural Language Understanding to identify and remove explicit images and detect angry and inappropriate messages.

When you have completed this code pattern, you will understand how to:

• Create a chatbot that integrates with Slack through IBM Cloud Functions
• Use Watson Visual Recognition to detect explicit images (in beta)
• Use Watson Natural Understanding to detect emotions in a conversation
• Identify entities with Watson Natural Language Understanding

Flow

1. The user interacts with the Slack app and either sends a text or uploads an image.
2. A bot passes the text or image used in Slack to an IBM Cloud Functions API. The API is a call to an IBM Function that categorizes the text or images based on the response of Watson Visual Recognition or Watson Natural Language Processing.
3. Watson Visual Recognition categorizes the uploaded image using the default and explicit classifiers.
4. Watson Natural Language Processing categorizes the text if text is sent as part of the Slack communication.
5. IBM Cloud Functions receives the response, and if the text is not polite, the bot sends a message to the Slack user to be more polite using the Slack post message API. If an image that is considered explicit is used, the image is deleted by IBM Cloud Functions using the Slack files delete API.

Timelines : 8 weeks

Project will go through the phases of scope, design, coding, unit testing, UAT, Award(Go Live)

On Successfull Completion, you get following prize & certificates (Sample):

Winner will be chosen for each phase(scope,design,coding,unit testing,UAT,Go-Live) of the project, cash prize from CEW ′, certificate, cloud credits will be provided for each phase.