Udemy - Performing Sentiment Analysis On Customer Reviews and Twe...

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 1.4 GB
  • Uploaded By freecoursewb
  • Downloads 125
  • Last checked 1 week ago
  • Date uploaded 2 years ago
  • Seeders 1
  • Leechers 4

Infohash : 474CAB511AA61A470BDFB8A0731F2582717D14B2



Performing Sentiment Analysis On Customer Reviews & Tweets

https://DevCourseWeb.com

Published 11/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.35 GB | Duration: 2h 58m

Learn how to perform sentiment analysis and emotion detection using TextBlob, NLTK, BERT, VADER, NRCLex, MultinomialNB

What you'll learn
Learn how to perform sentiment analysis on customer review data using TextBlob
Learn how to analyze emotional aspect of customer reviews using EmoLex
Learn how to perform sentiment analysis on twitter post data using VADER
Learn how to analyze emotional aspect of tweets using NRCLex
Learn how to predict sentiment of a tweet using BERT
Learn how to predict sentiment of a tweet using Multinomial Naive Bayes
Learn how to identify keywords that are frequently used in positive and negative customer reviews
Learn how to find correlation between customer ratings and sentiment
Case study: applying sentiment analysis on customer review dataset and predict if a review is more likely to be positive, negative or neutral
Learn factors that contribute to bias in customer reviews
Learn how to clean dataset by removing missing rows and duplicate values
Learn the basic fundamentals of sentiment analysis and its practical applications

Requirements
No previous experience in sentiment analysis is required
Basic knowledge in Python and NLP

Files:

[ DevCourseWeb.com ] Udemy - Performing Sentiment Analysis On Customer Reviews and Tweets
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1 - Introduction
    • 1 - Introduction to the Course.mp4 (31.9 MB)
    • 2 - Sentiment-Analysis.pptx (1.8 MB)
    • 2 - Table of Contents.mp4 (18.6 MB)
    • 3 - Whom This Course is Intended for.mp4 (11.8 MB)
    10 - Finding Correlation Between Customer Rating and Sentiment
    • 13 - Finding Correlation Between Customer Rating and Sentiment.mp4 (89.8 MB)
    11 - Identifying Keywords That are Frequently Used in Positive Negative Review
    • 14 - Identifying Keywords That are Frequently Used in Positive Negative Review.mp4 (165.7 MB)
    12 - Analyzing Emotional Aspect of Customer Review with EmoLex
    • 15 - Analyzing Emotional Aspect of Customer Review with EmoLex.mp4 (71.6 MB)
    13 - Performing Sentiment Analysis on Hotel Review Data with TextBlob
    • 16 - Performing Sentiment Analysis on Hotel Review Data with TextBlob.mp4 (83.4 MB)
    14 - Analyzing Emotional Aspect of Tweets with NRCLex
    • 17 - Analyzing Emotional Aspect of Tweets with NRCLex.mp4 (147.5 MB)
    15 - Performing Sentiment Analysis on Twitter Post Data with VADER
    • 18 - Performing Sentiment Analysis on Twitter Post Data with VADER.mp4 (73.6 MB)
    16 - Predicting Tweet Sentiment with BERT
    • 19 - Predicting Tweet Sentiment with BERT.mp4 (113.4 MB)
    17 - Predicting Tweet Sentiment with Multinomial Naive Bayes
    • 20 - Predicting Tweet Sentiment with Multinomial Naive Bayes.mp4 (111.8 MB)
    18 - Conclusion Summary
    • 21 - Conclusion Summary.mp4 (69.5 MB)
    2 - Tools IDE and Datasets
    • 4 - Tools IDE and Datasets.mp4 (93.2 MB)
    3 - Introduction to Sentiment Analysis
    • 5 - Introduction to Sentiment Analysis.mp4 (39.9 MB)
    4 - How Sentiment Analysis Works
    • 6 - Case-Study-Sentiment-Analysis.png (683.0 KB)
    • 6 - Sentiment Analysis Case Study.mp4 (67.7 MB)
    5 - Factors That Contribute to Bias in Customer Review
    • 7 - Factors That Contribute to Bias in Customer Review.mp4 (24.2 MB)
    6 - Setting Up Google Colab IDE
    • 8 - Google Colab IDE.txt (0.0 KB)
    • 8 - Setting Up Google Colab IDE.mp4 (34.2 MB)
    7 - Finding Downloading Datasets From Kaggle
    • 9 - Finding Downloading Datasets From Kaggle.mp4 (82.8 MB)
    • 9 - Kaggle.txt (0.0 KB)
    8 - Project Preparation
    • 10 - Uploading Dataset to Google Colab.mp4 (8.7 MB)
    • 11 - Quick Overview of Hotel Review Dataset.mp4 (18.5 MB)
    • Datasets
      • Tweets.csv (3.3 MB)
      • hotel_reviews.csv (1.2 MB)
      __MACOSX Datasets
      • _Tweets.csv (0.3 KB)
      • _hotel_reviews.csv (0.3 KB)
      • _Datasets (0.2 KB)
      • 9 - Cleaning Dataset by Removing Missing Values Duplicates
        • 12 - Cleaning Dataset by Removing Missing Values Duplicates.mp4 (21.0 MB)
        • Bonus Resources.txt (0.4 KB)

There are currently no comments. Feel free to leave one :)

Code:

  • udp://tracker.torrent.eu.org:451/announce
  • udp://tracker.tiny-vps.com:6969/announce
  • http://tracker.foreverpirates.co:80/announce
  • udp://tracker.cyberia.is:6969/announce
  • udp://exodus.desync.com:6969/announce
  • udp://explodie.org:6969/announce
  • udp://tracker.opentrackr.org:1337/announce
  • udp://9.rarbg.to:2780/announce
  • udp://tracker.internetwarriors.net:1337/announce
  • udp://ipv4.tracker.harry.lu:80/announce
  • udp://open.stealth.si:80/announce
  • udp://9.rarbg.to:2900/announce
  • udp://9.rarbg.me:2720/announce
  • udp://opentor.org:2710/announce
CACHE ❓ RP-FALLBACK 📄 torrent 🕐 20 Feb 2026, 01:16:31 pm IST ⏰ 17 Mar 2026, 01:16:31 pm IST ✅ Valid for 24d 23h 🔄 Wait 10m