├── .gitignore
├── README.md
├── assets
    └── Machine Learning Presentation - ISABAINE LABRIJI.pdf
├── notebooks
    ├── Twitter Sentiment Analysis with Python.ipynb
    └── Twitter Sentiment Analysis, Team ISBAINE LABRIJI.ipynb
└── requirements.txt


/.gitignore:
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1 | /.idea
2 | /data/
3 | /notebooks/.ipynb_checkpoints/
4 | 


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/README.md:
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 1 | # Twitter Sentiment Analysis using Python 🐍 and NLP 📙
 2 | 
 3 | ## 🚀 **Project Overview**
 4 | 
 5 | Welcome to the **Twitter Sentiment Analysis** project! 🌟 Here, we dive into the captivating realm of Natural Language Processing (NLP) to analyze tweet sentiments using mighty machine learning techniques.
 6 | 
 7 | ## 📊 **Dataset**
 8 | 
 9 | Access the dataset here: [Sentiment140 Dataset](https://drive.google.com/file/d/19IeqXU96-kDt6wy1wTNyhWrIw1jbK2Kx/view?usp=sharing). 📂
10 | 
11 | ## 🛠️ **Methodology**
12 | 
13 | We wield the power of classifiers to craft an effective sentiment analysis model, evaluating their prowess with accuracy and F1 scores. 🔍
14 | 
15 | ## **Getting Started 🏁**
16 | 
17 | Follow these simple steps to set up and start working on the project:
18 | 
19 | 1. **Clone the Repository**:
20 |    ```bash
21 |    git clone https://github.com/labrijisaad/Twitter-Sentiment-Analysis-with-Python.git
22 |    ```
23 |    
24 | 2. **Navigate to the Project Directory**:
25 |    ```bash
26 |    cd Twitter-Sentiment-Analysis-with-Python
27 |    ```
28 |    
29 | 3. **Check Python Version**: Ensure that you have Python 3.9 installed. You can find the required packages in the `requirements.txt` file.
30 | 
31 | 4. **Create a Virtual Environment** (recommended for project isolation):
32 |    ```bash
33 |    python3 -m venv venv
34 |    ```
35 |    
36 | 5. **Activate the Virtual Environment**:
37 | 
38 |    - For macOS/Linux:
39 |      ```bash
40 |      source venv/bin/activate
41 |      ```
42 |    
43 |    - For Windows:
44 |      ```bash
45 |      venv\Scripts\activate
46 |      ```
47 | 
48 | 6. **Install Dependencies** from `requirements.txt`:
49 |    ```bash
50 |    pip install -r requirements.txt
51 |    ```
52 | 
53 | 7. **Download the Dataset**:
54 |    Download the dataset from [Sentiment140 Dataset](https://drive.google.com/file/d/19IeqXU96-kDt6wy1wTNyhWrIw1jbK2Kx/view?usp=sharing) and place the CSV file in a newly created `data` directory within the project.
55 | 
56 | 8. **Launch Jupyter Notebook**:
57 |    Start the Jupyter Notebook server:
58 |    ```bash
59 |    jupyter notebook
60 |    ```
61 | 
62 | 
63 | 
64 | ## 🙏 **Acknowledgments**
65 | 
66 | This project was inspired by the helpful work of [analyticsvidhya](https://www.analyticsvidhya.com/). 🎩🙌
67 | 
68 | ## 📞 **Contact**
69 | 
70 | For any queries, suggestions, or virtual high-fives, feel free to reach out at **labrijisaad@gmail.com**. 📬
71 | 
72 | 


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/assets/Machine Learning Presentation - ISABAINE LABRIJI.pdf:
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https://raw.githubusercontent.com/labrijisaad/Twitter-Sentiment-Analysis-with-Python/c3efda74d2daff9d80956f8646304889ee1ae74e/assets/Machine Learning Presentation - ISABAINE LABRIJI.pdf


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/requirements.txt:
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 1 | # Python 3.9
 2 | numpy
 3 | pandas
 4 | regex
 5 | seaborn
 6 | wordcloud
 7 | matplotlib
 8 | nltk
 9 | scikit-learn
10 | wordnet
11 | notebook


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