EDA Projects

Analyzing restaurant reviews from Zomato to understand customer preferences and trends.

Exploring sales data from a supermarket to gain insights into product performance and customer behavior.

Analyzing Black Friday sales data to uncover shopping trends and patterns.

Building a linear regression model to predict house prices based on various features.

Customer Shopping Trends Analysis.

Investigating customer shopping behaviors and preferences to improve marketing strategies.

Applying machine learning to predict passenger survival on the Titanic.

Building and training neural networks to recognize handwritten digits.

To explore any of these projects, simply click on the corresponding link above, which will take you to the Jupyter Notebook file. You can view the code, visualizations, and analysis within each notebook.

To run these notebooks and reproduce the results, you will need to have the following software and libraries installed:

Python (recommended version 3.7 or higher)

Jupyter Notebook

NumPy

Pandas

Matplotlib

Seaborn

Scikit-Learn (for machine learning projects)