تعلم الآلة باستخدام Python: انشئ نموذج توقع مغادرة العملاء

This guided project aims to equip you with the skills to build a machine learning model for predicting customer churn in a bank using Python. You will start by exploring historical customer data, cleaning, and analyzing it using the Pandas library. Then, visualize the data using Matplotlib and Seaborn to understand the customer behavior better. Next, you will build three machine learning models capable of predicting customer churn using Scikit-learn and evaluate their accuracy and efficiency.

Throughout the practical project, you will be able to analyze customer data to address the bank's inquiries and present the results in a report using Jupyter notebook. You will also learn to identify the most important features that will aid in building the machine learning model for predicting customer churn. Additionally, you will gain an understanding of how each algorithm works, how to apply and evaluate them, and how to determine the best algorithm for this project.

• Explore and analyze historical customer data using the Pandas library to better understand the customers
• Visualize and present data using the Matplotlib and Seaborn libraries and calculate the correlation between variables and customer churn
• Build three machine learning models capable of predicting customer churn using the Scikit-learn library and evaluate their accuracy and efficiency