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所在平台: Udemy |
课程主页: https://www.udemy.com/course/chatbot-building-rasa-dialogflow-witai-python/
课程评论：没有评论
课程名称：使用Rasa构建聊天机器人 课程概述：你想要创建一个能够与访客互动的对话聊天机器人吗？在本教程中，你将学习如何使用Rasa NLU和Rasa Core来创建Python聊天机器人。这两个工具提供了多个自然语言处理功能，能够解析用户输入并匹配到正确的响应。将自然语言处理整合到聊天机器人中可能会很困难，但使用Rasa可以更轻松地创建Facebook Messenger机器人或网站聊天机器人。Rasa是一个强大的开源机器学习框架，旨在帮助开发者创建上下文聊天机器人，并使其功能超越简单问答。 在课程中，你将学习到Rasa NLU和Rasa Core。Rasa NLU是一个开源自然语言处理工具，用于意图分类和实体提取。可以将其视为一个高层API集合，帮助你使用现有的NLP和机器学习库构建自己的语言解析器。使用开源NLU的主要原因包括：1）你无需将所有聊天机器人训练数据交给Google、Microsoft、Amazon或Facebook；2）机器学习不是一刀切的。你可以根据自己的训练数据调整和定制Python聊天机器人模型；3）Rasa NLU可以在你希望的任何地方运行，因此你无需对每条聊天消息进行额外的网络请求。 Rasa Core利用开发者现有的领域知识，帮助其从零训练数据开始。它采用交互式学习方法，你手动指定聊天机器人可以说和做的所有事情，称为“动作”。一个动作可能是向用户打招呼，另一个可能是调用API或查询数据库。接着，你将训练一个概率模型，以预测在聊天记录的历史基础上，Python聊天机器人应该采取的动作。 本Python聊天机器人课程将帮助你： - 使用Rasa NLU和Rasa Core构建聊天机器人 - 理解意图和实体 - 构建Facebook Messenger机器人 - 在Heroku等云平台上部署聊天机器人
Do you want to create a talking chatbot that interacts with your visitors? In this tutorial, you will learn how to create Python chatbots using Rasa NLU and Rasa Core. They provide several Natural Language processing functions that parse user input and match it to the right response. Integrating NLP into your bot can be difficult, but with Rasa, it is much easier to create a Facebook Messenger bot or a website chatbot.Rasa is a powerful open-source machine learning framework for developers to create contextual chatbots and expand bots beyond answering simple questions. In this course, you will study both Rasa NLU and Rasa Core.Rasa NLU is an open-source natural language processing tool for intent classification and entity extraction in chatbots. You can think of it as a set of high-level APIs for building your own language parser using existing NLP and ML libraries. Among the main reasons for using open-source NLU are: 1) you don't have to hand over all your chatbot training data to Google, Microsoft, Amazon, or Facebook; 2) Machine Learning is not one-size-fits-all. You can tweak and customize Python chatbot models for your training data; and 3) Rasa NLU runs wherever you want, so you don't have to make an extra network request for every chatbot message that comes in.Rasa Core leverages developers' existing domain knowledge to help them bootstrap from zero training data, and adopts an interactive learning approach. With Rasa Core, you manually specify all the things your bot can say and do. We call these actions. One action might be to greet the user, another might be to call an API, or query a database. Then you train a probabilistic model to predict which action your Python chatbot should take given the history of a chatbot conversation.This Python chatbot course will help you:Build chatbots with Python using Rasa NLU & Rasa CoreUnderstand intents and entities.Build a Facebook Messenger bot.Deploy chatbots on cloud platforms such as Heroku.
