Welcome to the Twitter Sentiment Analysis project! ๐ Here, we dive into the captivating realm of Natural Language Processing (NLP) to analyze tweet sentiments using mighty machine learning techniques.
Access the dataset here: Sentiment140 Dataset. ๐
We wield the power of classifiers to craft an effective sentiment analysis model, evaluating their prowess with accuracy and F1 scores. ๐
Follow these simple steps to set up and start working on the project:
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Clone the Repository:
git clone https://github.com/labrijisaad/Twitter-Sentiment-Analysis-with-Python.git
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Navigate to the Project Directory:
cd Twitter-Sentiment-Analysis-with-Python
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Check Python Version: Ensure that you have Python 3.9 installed. You can find the required packages in the
requirements.txt
file. -
Create a Virtual Environment (recommended for project isolation):
python3 -m venv venv
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Activate the Virtual Environment:
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For macOS/Linux:
source venv/bin/activate
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For Windows:
venv\Scripts\activate
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Install Dependencies from
requirements.txt
:pip install -r requirements.txt
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Download the Dataset: Download the dataset from Sentiment140 Dataset and place the CSV file in a newly created
data
directory within the project. -
Launch Jupyter Notebook: Start the Jupyter Notebook server:
jupyter notebook
This project was inspired by the helpful work of analyticsvidhya. ๐ฉ๐
For any queries, suggestions, or virtual high-fives, feel free to reach out at [email protected]. ๐ฌ