Sentiment-Analysis-and-Classification-of-US-Airlines-from-Passenger-Tweets kyr0 · COMPLETED
Sentiment Analysis and a Classification Problem solved using machine learning algorithms like Logistic Regression, Support Vector Machines, XgBOOST, Random Forests Classifier, Niave Bayes . Cleaned textual tweets using techniques like Lowercasing, Stopword Removal, Lemmatization. Applied word2Vec,by generating word embeddings using pre-trained word
github.com/kyr0/Sentiment-Analysis-and-Classification-of-US-Airlines-from-Passenger-Tweets · ★ 0 · Forks 0 · Size 4.0 MB
SUMMARY
Technologies 1
Scored 1
Observed 1
Practices 6
Evidence 1
Skips 0
COVERAGE
Analyzed 4 files · 13 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2021-08-12
Last commit 2022-01-25
Active months 3
Commits 13