Mastering Chatbots with Botpress, Transformers, RAG & LLMs
Mastering Chatbots with Botpress, Transformers, RAG & LLMs, available at $74.99, has an average rating of 4.68, with 158 lectures, based on 211 reviews, and has 6622 subscribers.
You will learn about 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. Learn the Concepts of Prompt Engineering using LangChain, ChatGPT and HuggingFace 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. This course is ideal for individuals who are For those who want to learn how to build an intelligent digital assistants (chatbots) using open source tools It is particularly useful for For those who want to learn how to build an intelligent digital assistants (chatbots) using open source tools.
Enroll now: Mastering Chatbots with Botpress, Transformers, RAG & LLMs
Summary
Title: Mastering Chatbots with Botpress, Transformers, RAG & LLMs
Price: $74.99
Average Rating: 4.68
Number of Lectures: 158
Number of Published Lectures: 142
Number of Curriculum Items: 158
Number of Published Curriculum Objects: 142
Original Price: $27.99
Quality Status: approved
Status: Live
What You Will 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.
- Learn the Concepts of Prompt Engineering using LangChain, ChatGPT and HuggingFace
- 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.
Who Should Attend
- For those who want to learn how to build an intelligent digital assistants (chatbots) using open source tools
Target Audiences
- For those who want to learn how to build an intelligent digital assistants (chatbots) using open source tools
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?
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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.
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We’re NOT just going to talk only about the basics of chatbot development. We’re going to dive deeply into this world.
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This course is full of project-based tutorials. A lot of techniques will be derived via developing a set of chatbot projects
Chatbots 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, SetFit, GLiNER, Transformers, langChain, fastAPI, Docker,and more.
In this course, you will learn:
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How to Setup Your Development Environment Tools
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How to Install and start your first Botpressproject
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You will Understand what the conversation flow studio is
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Develop the different types of chatbot response templates
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You will learn how to Integrate with third parties and APIs to provide external information for users
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How to Develop a QnAchatbots
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Understand the problem intent detection and how to solve it using either rule-based or neural network techniques
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How to recognize entities in the user message and how to fill the slots.
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How to collect user data and forward them to an external API or store them in a database.
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How to develop your TransformersChatbot Assistant models (Rasa, SetFit and GLiNER)
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How to integrate Botpress with Rasa Chatbot Assistant
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How to develop a fastAPI app to serve your AI projects
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How to integrate your chatbot with popular messaging platforms like Facebook Messenger and Telegram
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How to use the modern Large Language Models (LLMs) like OpenAI to support your chatbots
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Learn all the basics of building a robust application using ChatGPTand open-source Large Language Models
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How to use Drage-Drop UI Toolslike Flowise to Develop LLM chatbots
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How to use LLMs to develop AI Engines and Chatbots
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Build the style of “Chat with your data” modern apps.
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Learn in detail how to build RAG LLM apps.
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More ..
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 chatbot projects and contribute to the rapidly evolving field of conversational AI.
Course Curriculum
Chapter 1: Course Introduction
Lecture 1: Course Introduction
Lecture 2: Install Botpress Locally using VirtualBox (faster & optional)
Chapter 2: Installing Docker
Lecture 1: Introduction
Lecture 2: Ubuntu-1 | Install Docker
Lecture 3: Windows-1 | Install WSL2
Lecture 4: Windows-2 | Install Docker
Lecture 5: Windows-3 | How to use WSL
Lecture 6: Docker Files
Chapter 3: Setup Basic Tools
Lecture 1: Setup MiniConda
Lecture 2: Setup JupyterLab
Lecture 3: How to use JupyterLab
Lecture 4: Conclusion
Chapter 4: BotPress Basics
Lecture 1: Introduction
Lecture 2: Why to Use BotPress
Lecture 3: Install, Update and Debug BotPress using Docker
Lecture 4: Your First Chatbot
Lecture 5: Hello Buddy Chatbot – Part 1/2
Lecture 6: Hello Buddy Chatbot – Part 2/2
Lecture 7: Variable Types
Lecture 8: Conclusion
Chapter 5: USA Population Chatbot
Lecture 1: Introduction
Lecture 2: API Supported Chatbot
Lecture 3: Data Validation Action
Lecture 4: Debugging Action Logs
Lecture 5: Sub Flows
Lecture 6: Choices Skill
Lecture 7: Conclusion
Chapter 6: API Actions
Lecture 1: Develop an API Action
Lecture 2: Custom Fallbacks
Chapter 7: Response Templates
Lecture 1: Introduction
Lecture 2: Texts and Images
Lecture 3: Cards
Lecture 4: Carousels
Lecture 5: Files
Lecture 6: Dropdown Menus
Lecture 7: Videos
Lecture 8: Conclusion
Chapter 8: Questining and Answering (QnA) Chatbots
Lecture 1: Introduction
Lecture 2: Feeding Inputs
Lecture 3: Train the QnA Chatbot
Lecture 4: Exporting and Importing Training Data
Lecture 5: Rich Answers
Lecture 6: Conclusion
Chapter 9: Botpress NLU Engine
Lecture 1: Introduction
Lecture 2: Introduction to Intent and Entity Recognition
Lecture 3: Botpress Intent Dection
Lecture 4: Botpress Entity Recognition
Lecture 5: Conclusion
Chapter 10: Restaurant Survey Chatbot
Lecture 1: Introduction
Lecture 2: Basic Chatbot Developing- Part 1/4
Lecture 3: Basic Chatbot Developing- Part 2/4
Lecture 4: Basic Chatbot Developing- Part 3/4
Lecture 5: Basic Chatbot Developing- Part 4/4
Lecture 6: Setup PgAdmin
Lecture 7: Setup Feedbacks Database
Lecture 8: Storing Feedbacks into Database 1/2
Lecture 9: Storing Feedbacks into Database 2/2
Lecture 10: Conclusion
Chapter 11: NLP Basics
Lecture 1: Introduction
Lecture 2: Introduction to Neural Networks
Lecture 3: Introduction to Text Representation
Lecture 4: Conclusion
Chapter 12: [NEW] Football API Project 1/2 | SetFit + GLiNER NLU Parsers
Lecture 1: IMPORTANT – Before you start
Lecture 2: What will you learn ?
Lecture 3: Football Chatbot Project Study
Lecture 4: How to train a SetFit model for Intent Detection
Lecture 5: How to use GLiNER for Entity Detection
Lecture 6: FastAPI Football Project – Pt1
Lecture 7: FastAPI Football Project – Pt2
Lecture 8: FastAPI Football Project – Pt3
Lecture 9: FastAPI Football Project – Pt4
Lecture 10: FastAPI Football Project – Pt5
Lecture 11: FastAPI Football Project – Pt6
Chapter 13: [NEW] Football API Project 2/2 | SetFit + GLiNER NLU Parsers
Lecture 1: IMPORTANT | Before you start
Lecture 2: Introduction
Lecture 3: Botpress Chatbot 1/6
Lecture 4: Botpress Chatbot 2/6
Lecture 5: Botpress Chatbot 3/6
Lecture 6: Botpress Chatbot 4/6
Lecture 7: Botpress Chatbot 5/6
Lecture 8: Botpress Chatbot 6/6
Lecture 9: Conclusion
Chapter 14: [DEPRECATED] Rasa NLU
Lecture 1: Important | Before you start
Lecture 2: Introduction
Lecture 3: Why Rasa
Lecture 4: Introduction to Intent and Entity Recognition
Instructors
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Abu Bakr Soliman
Machine Learning and NLP Developer
Rating Distribution
- 1 stars: 7 votes
- 2 stars: 1 votes
- 3 stars: 14 votes
- 4 stars: 51 votes
- 5 stars: 138 votes
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