Customer churn is a significant challenge for subscription-based businesses. The goal of this project is to develop a machine learning model that predicts which customers are likely to cancel their subscriptions. By analyzing historical data, including customer interactions, payment history, and engagement levels, businesses can implement strategies to retain customers. The project involves data preprocessing, exploratory data analysis (EDA), feature selection, model training, evaluation, and deployment of a predictive model.
Programming Languages: Python, R, SQL Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, TensorFlow/Keras (for deep learning models) Software/Tools: Jupyter Notebook or Google Colab, Tableau (for visualization), AWS/Azure (for cloud-based solutions), PostgreSQL/MySQL (for database management) Before Commencing the project the following links have to be examined.
https://www.kaggle.com/
https://www.tensorflow.org/
https://towardsdatascience.com/
https://scikit-learn.org/stable/
