How to Predict and Prevent Customer Loss Using AI

Understanding customer churn and its business implications. Overview of predictive analytics for churn prediction.

Introduction to the customer churn dataset. Data cleaning and preprocessing techniques.

Introduction to Artificial Neural Networks. Building and training the ANN model using TensorFlow/Keras.

Evaluating the model using precision, recall, and accuracy. Understanding and interpreting the confusion matrix and classification report.

Addressing participant questions and discussing further resources. Closing remarks and feedback collection.