Skip to content

garima24112000/Sentiment-Analysis

View on GitHub ↗Related repositories →

Built a deep learning model for sentiment classification in the movie review domain. The architecture included a word embedding layer to represent text data, an LSTM layer for sequence processing, and a classification layer for predicting sentiment. The model effectively classified reviews as positive or negative based on textual input.

active 2024-09-152024-09-15 (UTC)

Complete coverage27,129 / 27,131 hourly files (100%) · 2 absent upstream2023-08-152026-09-18 (UTC)
Events
2
Pushes
0
Pull requests
0
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 1 days from 2024-09-15 to 2024-09-15. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

Nobody pushed, opened or commented here in the loaded window — this repo's activity is stars and forks only.

Recent activity

Latest issues, pull requests and releases

No issue or PR events — this repo's activity is pushes only.

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.