swilliamc / NLP_Twitter_Sentiment_Analysis

NLP Twitter Sentiment Analysis (Machine Learning)

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NLP_Twitter_Sentiment_Analysis

NLP Twitter Sentiment Analysis (Machine Learning)

Completed Coursera Guided Project by Suhaimi William Chan

Instructor: Ryan Ahmed, Ph.D.

Project Structure

The hands on project on Twitter Sentiment Analysis is divided into following tasks:

Task #1: Understand the Problem Statement and business case

Task #2: Import libraries and datasets

Task #3: Perform Exploratory Data Analysis

Task #4: Plot the word cloud

Task #5: Perform data cleaning - removing punctuation

Task #6: Perform data cleaning - remove stop words

Task #7: Perform Count Vectorization (Tokenization)

Task #8: Create a pipeline to remove stop-words, punctuation, and perform tokenization

Task #9: Understand the theory and intuition behind Naive Bayes classifiers

Task #10: Train a Naive Bayes Classifier

Task #11: Assess trained model performance