customer-churn-prediction

There are 125 repositories under customer-churn-prediction topic.

  • archd3sai/Customer-Survival-Analysis-and-Churn-Prediction

    In this project, I have utilized survival analysis models to see how the likelihood of the customer churn changes over time and to calculate customer LTV. I have also implemented the Random Forest model to predict if a customer is going to churn and deployed a model using the flask web app.

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  • Pradnya1208/Telecom-Customer-Churn-prediction

    Customers in the telecom industry can choose from a variety of service providers and actively switch from one to the next. With the help of ML classification algorithms, we are going to predict the Churn.

    Language:Jupyter Notebook702121
  • DataVisualizationExpert/Customer-Churn-Analysis-using-Power-BI

    Unlock actionable insights and boost customer retention with this Power BI project. Analyze and visualize risk factors to proactively prevent churn. ➡️

  • satz2000/End-to-end-project---Customer-churn

    End to end projects-- Customer Churning prediction using Gradient Boost Classifier Algorithm perform pre-processing steps then fit data into the Algorithm and Hyper Parameter Tunning to reduce TN & FN value to perform our model to works with a new data. Finally deploying the model using Flask API

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  • himanshu-03/Customer-Churn-Prediction

    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.

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  • blackbird71SR/Small-Deep-Learning-Projects

    Small projects with Deep Learning magic! - Predicting Customer Churn in Banking, Predict tags on Stack Overflow, Sign Language Recognition

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  • Lab-of-Infinity/Datatrained-Projects

    Data Science Projects done at Data Trained Education during PG Data Science & ML Course

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  • Pegah-Ardehkhani/Customer-Churn-Prediction-and-Analysis

    Analysis and Prediction of the Customer Churn Using Machine Learning Models (Highest Accuracy) and Plotly Library

    Language:Jupyter Notebook9204
  • curiousily/Customer-Churn-Detection-with-TensorFlow-js

    Customer churn prediction using Neural Networks with TensorFlow.js

    Language:JavaScript8106
  • FirasKahlaoui/customer-churn

    This project aims to predict customer churn using machine learning techniques. By analyzing historical customer data, the model identifies patterns that indicate whether a customer is likely to leave. This can help businesses take proactive measures to retain customers and reduce churn rates.

    Language:Jupyter Notebook722
  • grknc/Customer-Churn-Analyzer-with-ML

    Telco Churn Analysis and Modeling is a comprehensive project focused on understanding and predicting customer churn in the telecommunications industry. Utilizing advanced data analysis and machine learning techniques, this project aims to provide insights into customer behavior and help develop effective strategies for customer

    Language:Jupyter Notebook6101
  • ahmedshahriar/Customer-Churn-Prediction

    Extensive EDA of the IBM telco customer churn dataset, implemented various statistical hypotheses tests and Performed single-level Stacking Ensemble and tuned hyperparameters using Optuna.

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  • alfarias/customer-churn-prediction

    Customer Churn Prediction using PyCaret.

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  • virajbhutada/telecom-customer-churn-prediction

    Predict and prevent customer churn in the telecom industry with our advanced analytics and Machine Learning project. Uncover key factors driving churn and gain valuable insights into customer behavior with interactive Power BI visualizations. Empower your decision-making process with data-driven strategies and improve customer retention.

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  • harishb1407/crm-using-ai-ml

    Transforming CRM using AI/ML

    Language:Jupyter Notebook4100
  • PeterSchuld/Stanford-BUS139W-DataDrivenMarketing

    Stanford Continuing Studies course "Data-Driven Marketing" by Angel Evan, Consultant. Completed Winter 2017-2018

  • SharathHebbar/Marketing-Analytics

    Marketing Analytics

    Language:Jupyter Notebook4101
  • AtashfarazNavid/MachineLearing-ChurnModeling

    Machine-Learning-1

    Language:Jupyter Notebook3102
  • ejeej/Survival_Analysis_Customers_Churn

    Predicting customers' churn with survival analysis, including time-dependent variables

    Language:R3100
  • shrutibalan4591/E-commerce-Customer-Churn-Prediction

    This is an end-to-end ML project, which aims at developing a classification model for predicting if a customer for an ecommerce business will churn or not in the following month

    Language:Jupyter Notebook3102
  • yash2189/Customer-Churn-Prediction-ML

    The objective is to build a classifier for prediction of customer churn.

    Language:Jupyter Notebook3204
  • fatianzh/customer-churn-prediction

    Hello, this is my final project with my friend when I joined Fresh Graduate Academy Program at Binar Academy in 2023.

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  • GaneshKotaSLU/Customer-Churn-Prediction

    The core purpose of this study is to find the impact of Sentiment Analysis in predicting customer churn for the e-commerce industry by employing different predictive models. Furthermore, the study is also focused on observing which model is best in a more accurate prediction for determining the churn rate of customers.

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  • johnathon-smith/telco_churn_project

    The goal of this project was to utilize classification models to predict whether or not a customer would churn. I went through the entire machine learning pipeline, discovered drivers of churn, and created many different models. Ultimately, my best Random Forest Classifier model was able to predict churned customers with an accuracy of about 80%.

    Language:Jupyter Notebook2100
  • Rajarshi12321/Customer-Churn

    Welcome to the Customer Churn Prediction repository, which is a Customer Churn Prediction Flask app repository! This app is designed to predict customer churn a trained model with 90% accuracy.

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  • saibattula93/Customer-churn-prediction

    Developing a customer churn prediction model using machine learning techniques. The model identifies potential churners by analyzing historical customer data, aiding businesses in retaining customers and boosting satisfaction. Evaluation based on accuracy, precision, recall, and F1 score. Emphasis on data quality and relevant features.

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  • SharathHebbar/Customer-Churn-ANN

    Customer-Churn-ANN

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  • sharmeen-k/Customer-Churn-Prediction

    A logistic regression model was used from the sk-learn library to predict customer churn on a telecomms dataset. The final model yielded the following indices: Best hyperparameter 'solver' = 'liblinear'; f1 score = 0.62 and log loss = 0.65.

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  • sharmi1206/telecom-customer-segmentation

    Telecom Customer segmentation and Churn Prediction

    Language:Jupyter Notebook2103
  • ShehaniWageesha/Customer-Churn-Machine-Learning

    Customer churn machine learning model that predicts whether a company's customers will stay with the company or not.

    Language:Jupyter Notebook2100
  • sylviahangnguyen/Customer-Churn-Prediction-SAS-Vyia

    The purpose of this assignment is to use SAS Machine Learning Platform - SAS Vyia to explore data, preform customer segmentation and predict customer churn.

  • churn-buster

    zander1268/churn-buster

    This project focuses on a fictitious software company, Churn Buster, that is pitching their tool to Telecom Inc., a fictitious wireless service company. Churn Buster has built a predictive model to reduce Telecom Inc.'s customer churn

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  • chatterjee007-dev/Deep_Learning

    Showcasing advanced deep learning projects utilizing CNNs and RNNs for tasks like image classification, customer churn prediction, and fake news detection. Demonstrates expertise in data preprocessing, model building, training, and evaluation to solve real-world problems.

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  • M3GHAN/Customer-Churn-Prediction-RFM-Logistic-Regression

    This project implements a customer churn prediction model using Recency, Frequency, and Monetary (RFM) analysis. It classifies customers into "Churned" or "Retained" categories using a logistic regression model based on customer behavior. The model helps businesses identify at-risk customers and design targeted retention strategies.

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