Welcome to the Sentiment Analysis on Food Reviews project repository!
The primary objectives of this project are:
- Develop a sentiment analysis model capable of accurately classifying the sentiment (positive, negative, or neutral) of food reviews.
- Explore different techniques and algorithms for sentiment analysis, such as machine learning models, deep learning models, or lexicon-based approaches.
- Evaluate the performance of the sentiment analysis model using appropriate metrics and benchmarks.
- Provide insights and visualizations on the sentiments expressed in food reviews, potentially identifying trends or patterns.
To run the code in this repository, follow these steps:
-
Clone the repository to your local machine: git clone https://github.com/your-username/Sentiment-Analysis-on-Food-Reviews.git
-
Navigate to the project directory: cd Sentiment-Analysis-on-Food-Reviews
- Explore the provided notebooks to understand the data preprocessing, model development, and evaluation process.
- Modify the code or experiment with different algorithms and techniques to improve the sentiment analysis model.
- Use the trained model to perform sentiment analysis on new food reviews or datasets.
- Refer to the documentation within the notebooks for detailed explanations of each step and function.
Contributions to the project are welcome! If you have any ideas for improvements, bug fixes, or new features, feel free to open an issue or submit a pull request.
use it as you wish
For any questions or inquiries about the project, feel free to contact [email protected].
Thank you for your interest in Sentiment Analysis on Food Reviews! I hope this project provides valuable insights into understanding customer sentiments in the food industry.