Johns Hopkins University

Chatbots

本课程是 Social Computing 专项课程 的一部分

Ian McCulloh

位教师:Ian McCulloh

包含在 Coursera Plus

深入了解一个主题并学习基础知识。
中级 等级

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1 周 完成
在 10 小时 一周
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深入了解一个主题并学习基础知识。
中级 等级

推荐体验

1 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Explore the history and mechanics of chatbots, enhancing your understanding of their design and function.

  • Construct and evaluate machine learning classifiers using BERT for effective text classification tasks.

  • Gain hands-on experience in creating and configuring functional chatbots using AWS Chatbot services.

要了解的详细信息

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作业

8 项作业

授课语言:英语(English)

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积累特定领域的专业知识

本课程是 Social Computing 专项课程 专项课程的一部分
在注册此课程时,您还会同时注册此专项课程。
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  • 获得对主题或工具的基础理解
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该课程共有4个模块

This course explores the practical applications of machine learning through hands-on modules covering data pre-processing, feature extraction, model evaluation, and supervised learning techniques. It delves into specialized topics such as computer vision and learning to implement and assess various machine learning models. This course combines theoretical insights with practical lab activities to equip you with essential skills in applied machine learning.

涵盖的内容

1篇阅读材料1个插件

In this module, you will delve into the fascinating world of chatbots, covering their historical development and evolution. You will understand the basic mechanics behind how chatbots work and explore fundamental design principles essential for enhancing their performance. You will gain practical insights into building and optimizing chatbots using Amazon Lex, a leading platform for developing conversational interfaces. By the end of this module, you will have a comprehensive understanding of chatbot technology and its application across various industries.

涵盖的内容

2个视频2篇阅读材料3个作业

In this module, you will focus on constructing and evaluating machine learning (ML) classifiers using crowdsourced data. You will learn how to leverage BERT (Bidirectional Encoder Representations from Transformers) in R and TensorFlow for text classification tasks. You will also gain hands-on experience in building ML models that classify text data effectively. You will learn to calculate and interpret ML performance metrics to assess classifier accuracy and reliability. By the end of this module, you will be equipped with practical skills to develop robust classifiers capable of handling diverse datasets.

涵盖的内容

1篇阅读材料2个作业1个非评分实验室

This module will guide you through the process of building your own chatbot using AWS (Amazon Web Services). You will begin with an introductory conceptual video outlining chatbot creation concepts. You will dive deep into practical implementation with AWS Chatbot, learning step-by-step how to set up and configure your chatbot. You will also explore strategies to make your chatbot operational and effective. You will collaborate with classmates to exchange ideas and troubleshoot challenges, fostering a supportive learning environment. By the end of this module, you will have the skills and confidence to develop functional chatbots tailored to various applications.

涵盖的内容

3篇阅读材料3个作业5个插件

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位教师

Ian McCulloh
Johns Hopkins University
17 门课程16,198 名学生

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