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所在平台: Udemy |
课程主页: https://www.udemy.com/course/mastering-chatbots-using-botpress-rasa-and-transformers/
课程评论：没有评论
课程名称：掌握使用 Botpress、Transformers、RAG 和 LLM 构建聊天机器人 概述： 您准备好从零开始学习如何构建强大的 AI 支持聊天机器人了吗？本课程与市面上其他许多聊天机器人开发课程有所不同：我们将不使用任何基于云的聊天解决方案，例如 Dialogflow、IBM Watson 或 Microsoft Azure，而是专注于同样强大且免费的开源技术。此外，我们不仅仅停留在聊天机器人开发的基础知识，而是深入探讨这一领域，课程内容丰富，以项目为基础的教程贯穿始终。 课程中，我们将探讨不同类型的聊天机器人及其应用案例，包括基于规则的聊天机器人、AI 驱动的聊天机器人及会话 AI。此外，还将覆盖构建聊天机器人所需的各种技术和平台，例如自然语言处理（NLP）、机器学习（ML）以及开源项目 Botpress、SetFit、GLiNER、Transformers、langChain、fastAPI、Docker 等。 在本课程中，您将学习： - 如何设置开发环境工具 - 如何安装并启动第一个 Botpress 项目 - 了解对话流程工作室 - 开发不同类型的聊天机器人响应模板 - 如何与第三方和 API 集成，为用户提供外部信息 - 开发问答聊天机器人 - 理解问题意图检测及其解决方案，包括基于规则或神经网络技术 - 识别用户消息中的实体及填充槽位 - 收集用户数据并转发至外部 API 或存入数据库 - 开发聊天助手模型（Rasa、SetFit 和 GLiNER） - 将 Botpress 与 Rasa 聊天助手集成 - 开发 fastAPI 应用以支持 AI 项目 - 将聊天机器人与流行的消息平台（如 Facebook Messenger 和 Telegram）集成 - 使用现代大型语言模型（LLMs），如 OpenAI，来支持聊天机器人 - 学习构建基于 ChatGPT 和开源大型语言模型的健壮应用的基础知识 - 利用拖放 UI 工具如 Flowise 开发 LLM 聊天机器人 - 使用 LLM 开发 AI 引擎和聊天机器人 - 构建“与您的数据对话”的现代应用程序 - 深入了解如何构建 RAG LLM 应用 课程结束时，学生将全面理解当前聊天机器人技术的现状及其在实际应用中的作用。这些知识将使学生具备将自己的聊天项目付诸实践的技能和信心，从而为快速发展的会话 AI 领域做出贡献。
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, SetFit, GLiNER, Transformers, langChain, 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 network techniquesHow to recognize entities in the user message and how to fill the slots.How to collect user data and forward them to an external API or store them in a database.How to develop your Transformers Chatbot Assistant models (Rasa, SetFit and GLiNER)How 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 TelegramHow to use the modern Large Language Models (LLMs) like OpenAI to support your chatbotsLearn all the basics of building a robust application using ChatGPT and open-source Large Language ModelsHow to use Drage-Drop UI Tools like Flowise to Develop LLM chatbotsHow to use LLMs to develop AI Engines and ChatbotsBuild the style of "Chat with your data" modern apps.Learn in detail how to build RAG LLM apps.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.
