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GitHub / Abdulraqib20 / Sentiment-Analysis-with-Student-Feedback
Sentiment analysis of student feedback in engineering education. The goal is to analyze and gain insights from student feedback data to understand their sentiments and identify areas for improvement. The sentiment analysis is performed using natural language processing techniques and machine learning algorithms to classify feedback data.
Stars: 8
Forks: 4
Open Issues: 1
License: None
Language: Jupyter Notebook
Repo Size: 26.7 MB
Dependencies:
29
Created: about 1 year ago
Updated: 6 months ago
Last pushed: 6 months ago
Last synced: 6 months ago
Files
Dependencies
- Keras-Preprocessing ==1.1.2
- Pillow ==9.3.0
- jax *
- jaxlib *
- keras ==2.9.0
- keras_nlp ==0.6.0
- matplotlib ==3.5.2
- matplotlib-inline ==0.1.3
- nest-asyncio ==1.5.5
- nltk ==3.7
- notebook ==6.4.12
- notebook-shim ==0.1.0
- numpy ==1.23.5
- packaging ==21.3
- pandas ==1.5.3
- plotly ==5.16.1
- protobuf >=3.19.4,<4
- scikit-learn *
- seaborn ==0.12.1
- semver ==2.13.0
- streamlit >=0.70.0,<1
- tenacity ==8.2.3
- tensorboard-data-server ==0.6.1
- tensorboard-plugin-wit ==1.8.1
- tensorflow >=2.0.0,<3
- tensorflow-estimator ==2.9.0
- tensorflow-io-gcs-filesystem ==0.26.0
- transformers ==4.25.1
- wordcloud ==1.8.2.2