Twitter-Sentiment-Analysis

This repository contains a Jupyter Notebook that delves into the process of sentiment analysis on Twitter data. From data preprocessing to model evaluation, each step of the machine learning pipeline is detailed.

Contents:

1. Initializing the Dependencies: Setting up the necessary libraries and tools required for the sentiment analysis process.
2. Data Cleaning and Preprocessing: The steps to preprocess and clean the Twitter data for better model performance.
3. Model Training and Evaluation: Building and evaluating the sentiment analysis model.

How to Use:

1. Clone the repository.
2. Install the required libraries as mentioned in the "Initializing the Dependencies" section.
3. Run the notebook cells sequentially to understand the sentiment analysis process.