文件列表:

Hackathon - GenAI BFSI - V2.0.pdf
LICENSE
main.ipynb
train.csv
train.xlsx
tweets

# BFSI Sentiment Analysis with NLP and Generative AI This repository contains code for a hackathon project aimed at predicting sentiment for financial news headlines using natural language processing (NLP) techniques and Generative AI models. ## Problem Statement The task is to develop a solution to predict sentiment for financial news headlines using NLP and Generative AI techniques. The primary goal is to accurately classify the sentiment of headlines as positive, negative, or neutral. ## Dataset The training dataset (`train.csv`) contains news headlines along with their sentiment labels. ## Code Structure - `main.ipynb`: Jupyter Notebook containing the code implementation. - `train.csv`: Training data file containing news headlines and their sentiment labels. ## Libraries Used - pandas: For data manipulation and analysis. - matplotlib: For data visualization. - NLTK: For natural language processing tasks. - wordcloud: For generating word clouds. - scikit-learn: For machine learning tasks. ## Usage 1. Clone the repository. 2. Ensure you have all the required libraries installed. You can install them using pip. 3. Run the `main.ipynb` notebook to execute the code. ## Results The code performs sentiment analysis on financial news headlines and provides insights into the sentiment distribution. Additionally, it includes a machine learning model to classify sentiment and evaluates its accuracy. ## Contribution Feel free to contribute to the project by opening issues or submitting pull requests. ## License This project is licensed under the [MIT License](https://github.com/shreyuu/BFSI-NLP-Hackathon/blob/master/LICENSE).

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