Chatbots enable the automation of many of mundane activities and enable manifold automation. Majority of the prominent chatbot platform require sharing confidential enterprise customer information. Here comes RASA a open source alternate to have complete control over the chatbot experience. RASA comes with two main components RASA NLU (Natural Language understanding) and RASA Core (Deep Learning based Natural language Generation). This talk focus on how we can utilize the Open source RASA Stack for building the CHATBOT and control the complete data, execution and conversation with in the enterprise environment. Talk also focus on the architectural components i.e: Natural Language processing, Deep learning frameworks and how we can configure the components of our own choice for building the conversational interface. Part of the Talk we will have a demo of how we can quickly build a chatbot from scratch.

 
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Outline/Structure of the Demonstration

Conversational AI Framework for building contextual chatbots and AI assistants.

Understanding Chatbot Architecture

Introduction to Current Chatbot Platforms and Industry Problem

Introduction to RASA Framework

introduction to RASA Chatbot Architecture

Natural Language understanding - Components

CORE Components and Structure.

Core - Stories and Dialog management

Integrating with External API

Demonstration using Restaurant Details capture details.

Demonstration integrating with Slack Messaging Platform.

Learning Outcome

- Understanding the architecture of how a chatbot solution can be build from basic to detailed understanding of implementation.

- Fine tuning Stories using Data processing and analyzing the data input.

- Pros and cons of using various NLP and Deep Learning approaches.

- Implementing in-house chatbot solution.

- Integrating with SLACK and External API services.

Target Audience

Conversational AI, Building Chat Bot, Open Source contributors, NLP engineers, Data Analysts

Prerequisites for Attendees

No prerequisites required but a basic understanding of chatbots and their application. Basic understanding of NLP, Deep learning added advantage.

schedule Submitted 4 weeks ago

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