Mastering Chatbots Using Botpress, Rasa And Transformers

All you need to develop your next AI Chatbot using Open-Source tools like Botpress, Rasa, Transformers and FastAPI

What you'll learn
Developing Chatbots using Open-Source tools like Botpress, Rasa and Transformers. No cloud based solutions.
Understand all of the Chatbot developing pillars like intent-detection, entity-recognition, conversation flow and more.
Develop Neural Networks models to detect entities and Recognize entities in the user messages.
Integrate with third parties and APIs to develop mature chatbots with live data.
Develop web applications using fastAPI to support the chatbot services.
Learn via developing a set of real-world chatbot projects.

Requirements
A big portion of this course does not require any programming skills. Just the basics of Python and JavaScript are required for the advanced levels

Description
Are you ready to learn how to build powerful and AI-supported chatbots from scratch?there are a lot of courses out there that teach you how to develop chatbots. So what makes this course DIFFERENT?We're NOT going to use any cloud-based chatbot solutions like Dialogflow, IBM Watson, or Microsoft Azure. Instead, we'll be focusing on free and open-source technologies that are just as robust and powerful.We're NOT just going to talk only about the basics of chatbot development. We’re going to dive deeply into this world.This course is full of project-based tutorials. A lot of techniques will be derived via developing a set of chatbot projectsChatbots are everywhere and are becoming an increasingly important part of our daily lives. They're used for a wide range of applications, from customer service to online shopping, and they're only getting more advanced and sophisticated.In the course, we delve into the different types of chatbots and their use cases, including rule-based chatbots, AI-powered chatbots, and conversational AI. We also cover the various technologies and platforms that are used to build chatbots, such as natural language processing (NLP), machine learning (ML), and chatbot development open-source projects like Botpress, Rasa, Transformers, fastAPI, Docker, and more.In this course, you will learn:How to Setup your development environment toolsHow to Install and start your first Botpress projectYou will Understand what the conversation flow studio isDevelop the different types of chatbot response templatesYou will learn how to Integrate with third parties and APIs to provide external information for usersHow to Develop a QnA chatbotsUnderstand the problem intent detection and how to solve it using either rule-based or neural networks techniquesHow to recognize entities in the user message and how to fill the slots.How to collect the data from users and forward them to an external API or store them in a database.How to develop your Rasa Chatbot Assistant modelsHow to integrate Botpress with Rasa Chatbot AssistantHow to develop a fastAPI app to serve your AI projectsHow to integrate your chatbot with popular messaging platforms like Facebook messenger and TelegramMore ...By the end of the course, students will have a comprehensive understanding of the current state of chatbot technology and how it is being used in real-world applications. This knowledge will equip students with the skills and confidence to embark on their own chatbot projects and contribute to the rapidly evolving field of conversational AI.

Overview
Section 1: Course Introduction

Lecture 1 Introduction

Section 2: Installing Docker

Lecture 2 Introduction

Lecture 3 Install Docker - Ubuntu

Lecture 4 Install Docker - Windows

Lecture 5 Using of WSL - Windows

Lecture 6 Docker Files

Section 3: Setup Basic Tools

Lecture 7 Setup MiniConda

Lecture 8 Setup JupyterLab

Lecture 9 How to use JupyterLab

Lecture 10 Conclusion

Section 4: BotPress Basics

Lecture 11 Introduction

Lecture 12 Why to Use BotPress

Lecture 13 Setup BotPress

Lecture 14 Your First Chatbot

Lecture 15 Hello Buddy Chatbot - Part 1/2

Lecture 16 Hello Buddy Chatbot - Part 2/2

Lecture 17 Variable Types

Lecture 18 Conclusion

Section 5: USA Population Chatbot

Lecture 19 Introduction

Lecture 20 API Supported Chatbot

Lecture 21 Data Validation Action

Lecture 22 Debugging Action Logs

Lecture 23 Sub Flows

Lecture 24 Choices Skill

Lecture 25 Conclusion

Section 6: API Actions

Lecture 26 Develop an API Action

Lecture 27 Custom Fallbacks

Section 7: Response Templates

Lecture 28 Introduction

Lecture 29 Texts and Images

Lecture 30 Cards

Lecture 31 Carousels

Lecture 32 Files

Lecture 33 Dropdown Menus

Lecture 34 Videos

Lecture 35 Conclusion

Section 8: Questining and Answering (QnA) Chatbots

Lecture 36 Introduction

Lecture 37 Feeding Inputs

Lecture 38 Train the QnA Chatbot

Lecture 39 Exporting and Importing Training Data

Lecture 40 Rich Answers

Lecture 41 Conclusion

Section 9: Botpress NLU Engine

Lecture 42 Introduction

Lecture 43 Introduction to Intent and Entity Recognition

Lecture 44 Botpress Intent Dection

Lecture 45 Botpress Entity Recognition

Lecture 46 Conclusion

Section 10: Restaurant Survey Chatbot

Lecture 47 Introduction

Lecture 48 Basic Chatbot Developing- Part 1/4

Lecture 49 Basic Chatbot Developing- Part 2/4

Lecture 50 Basic Chatbot Developing- Part 3/4

Lecture 51 Basic Chatbot Developing- Part 4/4

Lecture 52 Setup PgAdmin

Lecture 53 Setup Feedbacks Database

Lecture 54 Storing Feedbacks into Database 1/2

Lecture 55 Storing Feedbacks into Database 2/2

Lecture 56 Conclusion

Section 11: NLP Basics

Lecture 57 Introduction

Lecture 58 Introduction to Neural Networks

Lecture 59 Introduction to Text Representation

Lecture 60 Conclusion

Section 12: Rasa NLU

Lecture 61 Introduction

Lecture 62 Why Rasa

Lecture 63 Introduction to Intent and Entity Recognition

Lecture 64 Rasa Data Architecture

Lecture 65 Rasa Dataset 1/3

Lecture 66 Rasa Dataset 2/3

Lecture 67 Rasa Dataset 3/3

Lecture 68 Train a Rasa Model

Lecture 69 Conclusion

Section 13: Football Chatbot 1/2

Lecture 70 Introduction

Lecture 71 What will you build ?

Lecture 72 How to Plan the Project ?

Lecture 73 Train Rasa Model

Lecture 74 FastAPI Project 1/6

Lecture 75 FastAPI Project 2/6

Lecture 76 FastAPI Project 3/6

Lecture 77 FastAPI Project 4/6

Lecture 78 FastAPI Project 5/6

Lecture 79 FastAPI Project 6/6

Lecture 80 Conclusion

Section 14: Football Chatbot 2/2

Lecture 81 Introduction

Lecture 82 Botpress Chatbot 1/6

Lecture 83 Botpress Chatbot 2/6

Lecture 84 Botpress Chatbot 3/6

Lecture 85 Botpress Chatbot 4/6

Lecture 86 Botpress Chatbot 5/6

Lecture 87 Botpress Chatbot 6/6

Lecture 88 Conclusion

Section 15: Messaging Platforms Integration

Lecture 89 Introduction

Lecture 90 Botpress Integration

Lecture 91 Setup Ngrok - Ubuntu

Lecture 92 Setup Ngrok - Windows

Lecture 93 Facebook Integration

Lecture 94 Telegram Integration

Lecture 95 Website Integration

Lecture 96 Conclusion

For those who want to learn how to build an intelligent digital assistants (chatbots) using open source tools

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