CodeAlpha Internship Projects – Data Analysis & Machine Learning

This repository contains my solutions for CodeAlpha’s Internship Tasks in Python.
Each task demonstrates practical use of data analysis, data visualization, and machine learning.

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📂 Tasks Overview

✅ Task 1: Unemployment Analysis with Python

• Performed exploratory data analysis on Indian unemployment data.
• Visualized unemployment rates across regions and months using heatmaps and line plots.
• Libraries used: pandas, matplotlib.

✅ Task 2: EDA on Indian Unemployment Dataset

• Deep exploratory data analysis on the same dataset.
• Found trends by region and month, created pivot tables, and performed visual analysis.
• Libraries used: pandas, matplotlib.

✅ Task 3: Car Price Prediction with Machine Learning

• Collected car features like year, present price, fuel type, transmission.
• Trained a regression model (Random Forest Regressor) to predict car selling price.
• Performed preprocessing, feature engineering, and model evaluation.
• Libraries used: pandas, scikit-learn, matplotlib.

✅ Task 4: Sales Prediction using Python

• Predicted future sales based on advertising spend across TV, Radio, and Newspaper.
• Built a linear regression model to forecast sales.
• Analyzed how changes in advertising budget impact sales outcomes.
• Libraries used: pandas, scikit-learn, matplotlib.

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🛠 Requirements

Create a virtual environment and install the following:

bash pip install pandas scikit-learn matplotlib (Optional) For notebook use:

bash Copy code pip install jupyter 🚀 How to Run Clone this repository:

bash Copy code git clone cd Install requirements:

bash Copy code pip install -r requirements.txt Open each task’s Jupyter Notebook:

bash Copy code jupyter notebook Then run the corresponding .ipynb file for each task.