NLP: Twitter Sentiment Analysis

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在此指导项目中,您将:

Create a pipeline to remove stop-words, punctuation, and perform tokenization

Understand the theory and intuition behind Naive Bayes classifiers

Train a Naive Bayes Classifier and assess its performance

Clock2 hours
Beginner初级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

In this hands-on project, we will train a Naive Bayes classifier to predict sentiment from thousands of Twitter tweets. This project could be practically used by any company with social media presence to automatically predict customer's sentiment (i.e.: whether their customers are happy or not). The process could be done automatically without having humans manually review thousands of tweets and customer reviews. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

您要培养的技能

  • Artificial Intelligence (AI)
  • Python Programming
  • Machine Learning
  • Natural Language Processing

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Import libraries and datasets

  2. Perform Exploratory Data Analysis

  3. Plot the word cloud

  4. Perform data cleaning - removing punctuation

  5. Perform data cleaning - remove stop words

  6. Perform Count Vectorization (Tokenization)

  7. Create a pipeline to remove stop-words, punctuation, and perform tokenization

  8. Understand the theory and intuition behind Naive Bayes classifiers

  9. Train a Naive Bayes Classifier

  10. Assess trained model performance

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

授课教师

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