This app is used to perform an indepth analysis of a text The analysis sections include ->
1. Spam or Ham Detection
2. Sentiment Analysis
3. Stress Detection
4. Hate & Offensive Content Detection
5. Sarcasm Detection
- Python
-
Numpy
-
Pandas
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Streamlit
-
Scikit Learn
-
Tensorflow
- Each prediction page is conneceted with a Machine Learning Model which uses either of Logistic Regression, Decision Tree, Random Forest Algorithms to predict the results.
- Also we have 5 different datasets being used for each prediction.
- We can land into each prediction site of the web app from the options in the Navigation Menu.
- We have only 1 relevant feature taken into consideration which is the text and then the text is preprocessed and vectoized with help of TF-IDF Vectorizer to fit into the model and tain it.
- So the user gets a broad overview of the text after the analysis
| Text Analysis Type | Feature |
|---|---|
| Spam or Ham Detection Page | Text |
| Sentiment Analysis Page | Text |
| Stress Detection Page | Text |
| Hate & Offensive Content Page | Text |
| Sarcasm Detection | Text |
The text is preprocessed then fed to the model.
After the modeling part the model is deployed using Streamlit library on Streamlit Share so that the app is available for usage for everyone.
https://sanchari-text-miner.streamlit.app/
