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Implementing an AI Chatbot with Dialogflow

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Checkpoints

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Create a Dialogflow agent

Create Intents

Allow Fulfillment to Store Help Ticket Data

Tickets are Logged in Datastore

Implementing an AI Chatbot with Dialogflow

1시간 크레딧 9개

GSP078

Google Cloud Self-Paced Labs

Overview

Dialogflow is one of the hottest computer-human interaction platforms on the market. It offers all the services and complexities of natural language processing and machine learning, but uses a straightforward interface that allows you to start developing Assistant, Alexa, and Cortana integrated applications today. In this lab, you will build a Google Assistant chatbot that submits helpdesk tickets. The following is a diagram of the chatbot application on Google Cloud:

b4c6dcdb2577c898.png

The exercises are ordered to reflect a common cloud developer process. You will:

  • Set up your lab and learn how to work with Dialogflow and your Google Cloud environment.
  • Deploy a simple Dialogflow application.
  • Deploy a simple cloud function within Google Cloud to connect with Dialogflow.
  • Test your chatbot.

What you'll learn

By the end of this lab, you will have an understanding of the following:

  • Basics concepts and constructs of Dialogflow, including intent, entity and context.
  • Chatbot workflow.
  • Life of a conversation.

Prerequisites

This is an expert level lab. Before taking it, you should be comfortable with at least the basics of machine learning and natural language processing. Here are some Qwiklabs that can get you up to speed:

Once you are prepared, scroll down to dive into Dataflow.

이 실습의 나머지 부분과 기타 사항에 대해 알아보려면 Qwiklabs에 가입하세요.

  • Google Cloud Console에 대한 임시 액세스 권한을 얻습니다.
  • 초급부터 고급 수준까지 200여 개의 실습이 준비되어 있습니다.
  • 자신의 학습 속도에 맞춰 학습할 수 있도록 적은 분량으로 나누어져 있습니다.
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