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The Customer Churn table contains information on all 7,043 customers from a Telecommunications company in California in Q2 2022. We need to predict whether the customer will churn, stay or join the company based on the parameters of the dataset.

A Python project analyzing customer churn using Exploratory Data Analysis (EDA). Insights into demographic, behavioral, and financial factors influencing churn using real-world bank dataset.

Call Detail Record (CDR) is the information captured by the telecom companies during the Call, SMS and Internet activity. These information’s provides insights about the customer needs when it is used with customer demographics. Most of the telecom companies using call detail record information ... Read more

Telecom Customer Churn Analysis with Python

Customer Churn Analysis Experiments using Classical ML algorithms and Deep Neural Network

Application of K-means clustering. Prediction of customer churn using Multi-layer Perceptron ANN, Logistic Regression, SVM-RBF and Random Forest Classifier.

A sample Power BI report showcasing cohort analysis and customer churn in a retail setting.

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Causal Analysis of Customer Churn using DeepLearning

Comprehensive Power BI dashboards showcasing insights on Call Centre Trends, Customer Retention, and Diversity & Inclusion to drive business impact.