An interactive web application developed with Streamlit, designed for making predictions using various machine learning models. The app dynamically generates forms and pages from JSON configuration files. ⭐ If you found this helpful, consider starring the repo!
🔍 Problem Description:
Get the sentiments of the reviews
🧠 Model Description:
Used Logistic Regression model for implementation. It will classify the reviews into two classes, namely, positive and negative.
⏲️ Estimated Time for Completion:
Completed within 1 day
🎯 Expected Outcome:
It is used to classify the reviews made by the consumers into positive and negative.
📄 Additional Context:
To be Mentioned while taking the issue:
What is your participant role? GSSOC -24 EXTD, Hacktoberfest
Note:
Please review the project documentation and ensure your code aligns with the project structure.
Please ensure that either the predict.py file includes a properly implemented model_details() function or the notebook contains this function to print a detailed model report. The model will not be accepted without this function in place, as it is essential for generating the necessary model details.
Prefer using a new branch to resolve the issue, as it helps keep the main branch stable and makes it easier to manage and review your changes.
Strictly use the pull request template provided in the repository to create a pull request.
🔍 Problem Description: Get the sentiments of the reviews
🧠 Model Description: Used Logistic Regression model for implementation. It will classify the reviews into two classes, namely, positive and negative.
⏲️ Estimated Time for Completion: Completed within 1 day
🎯 Expected Outcome: It is used to classify the reviews made by the consumers into positive and negative.
📄 Additional Context:
To be Mentioned while taking the issue:
Note:
predict.pyfile includes a properly implementedmodel_details()function or the notebook contains this function to print a detailed model report. The model will not be accepted without this function in place, as it is essential for generating the necessary model details.