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srikarpk150/Emotion-Classification-using-NLP

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A text-based emotion classification project using NLP techniques to detect emotions like happiness, sorrow, and anger. It includes preprocessing, feature extraction (TF-IDF, Word2Vec), and model training with Logistic Regression and Random Forest. The model is fine-tuned with GridSearchCV and evaluated on unseen data for real-world applicability.

active 2024-09-19 → 2025-09-12 (UTC)

Complete coverage28,079 / 28,079 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-27 (UTC)
Events
2
Pushes
1
Pull requests
0
Issues
0
Stars
0
Forks
1

Activity over time

Daily event counts in the loaded window

Line chart, 359 days from 2024-09-19 to 2025-09-12. Pushes: 1 total, peak 1 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

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

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

ContributorContributionsPushesPRsComments
srikarpk1501100

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.