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Lesson 2: Tech Stack Used
This project uses the following technologies and tools:
1. Python: The core programming language used for data analysis and machine learning.
2. Google Colab: The platform used to write, execute, and share notebooks online.
3. Pandas: Used for loading the CSV file, cleaning data, handling missing values, feature engineering, and data manipulation.
4. NumPy: Used for numerical computations and array-based operations.
5. Matplotlib: Used to create visualizations such as bar charts and confusion matrix plots.
6. Seaborn: Used for statistical visualizations such as heatmaps.
7. Scikit-learn: Used to split the dataset, encode variables, build the Logistic Regression model, and evaluate model performance.
8. Gradio: Used to deploy the trained model into an interactive interface for real-time churn prediction.
These tools work together to transform raw customer data into meaningful insights and predictive outputs.










