GitHub / Sarthak-Mohapatra / US-Airlines-Tweets-Sentiment-Analysis
Classifying a tweet as positive, neutral, or negative sentiment using Natural Language Processing (CBOW approaches) and Traditional Machine Learning Algorithms.
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PURL: pkg:github/Sarthak-Mohapatra/US-Airlines-Tweets-Sentiment-Analysis
Stars: 1
Forks: 0
Open issues: 0
License: None
Language: Jupyter Notebook
Size: 1.76 MB
Dependencies parsed at: Pending
Created at: over 4 years ago
Updated at: over 1 year ago
Pushed at: about 4 years ago
Last synced at: over 1 year ago
Topics: bigram-model, count-vectorizer, lematization, logistic-regression, naive-bayes-algorithm, naive-bayes-classifier, nlp, onevsrestclassifier, python, sentiment-analysis, sentiment-classification, stemming, tf-idf, unigram-model, xgboost, xgboost-algorithm, xgboost-model