SALES PREDICTION

This is the Task 4 project for the CodSoft internship / assignment series. It demonstrates a data analysis and machine learning workflow using an advertising dataset.

Project Structure

CodSoft_Task4/ ├── main.ipynb # Jupyter notebook for analysis and modeling ├── advertising.csv # Dataset used in the notebook └── README.md # Project overview and instructions

Description

Load and inspect the advertising.csv dataset
Perform exploratory data analysis (EDA), distributions, correlations
Preprocess data (cleaning, encoding, scaling)
Build one or more ML models (e.g. regression, classification)
Evaluate model performance
Interpret results and draw conclusions

Requirements

Python 3.7+
Jupyter Notebook
Libraries: -pandas
-numpy
-matplotlib
-seaborn
-scikit-learn

Results & Outputs

📊 Results Best performing model: Random Forest Classifier. Achieved R² Score: 0.90.