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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.
Machine Learning/Pattern Recognition Models to analyze and predict if a client will subscribe for a term deposit given his/her marketing campaign related data
In this data set we have perform classification or clustering and predict the intention of the Online Customers Purchasing Intention. The data set was formed so that each session would belong to a different user in a 1-year period to avoid any tendency to a specific campaign, special day, user profile, or period.
A Data-Driven Approach to Predict the Success of Bank Telemarketing
Analysis and Prediction of the Customer Churn Using Machine Learning Models (Highest Accuracy) and Plotly Library
Recurrent Capsule Network for Text Classification
Clustering validation with ROC Curves
calculate ROC curve and find threshold for given accuracy
Репозиторий хранит лучшее решение команды-победителя Best Character для олимпиады НТИ
This project contains the data and code used in the paper: Denter, Nils M.; Aaldering, Lukas Jan; Caferoglu, Huseyin (2022): Forecasting future bigrams and promising patents: Introducing text-based link prediction. In Foresight ahead-of-print (ahead-of-print). DOI: doi.org/10.1108/fs-03-2021-0078.
2nd ranked at Cameroon - Fraud Detection in Electricity and Gas Consumption Challenge
Used the Global Terrorism Database to Explore Features of Suicide Bombings
League of Legends Game Data Analysis (Random Forest, KNN, SVM, XGB / Kaggle game data 2017)
Analysing the telecom customer churn data
Using various supervised learning estimators in Sci-Kit Learn to get the best prediction accuracy if possible for the pima indians dataset.
Ciência de Dados
The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit (variable y).
Predict fraudulent credit card transactions using TensorFlow, Keras, K Neighbors, Decision Tree, SVM Regression and Logistic Regression classifiers .
Evaluation of Machine Learning Models with Yellowbrick
Data analysis, visualization and prediction for the prevention of heart disease using ML models
simple script for plotting precision recall curves
A wide variety of supervised and unsupervised machine learning methods using the scikit-learn library
Учебные проекты курса "Специалист по Data Science", Яндекс Практикум
Building a convolutional neural network for MNIST dataset, including hyperparameter search, dropout regularization, and optimizer selection
Predict the intention of customer either subscribing to the product or not.
Estimated probability models that help target consumers to build brand loyalty
На основании данных о поведении клиентов построить модель с максимально большим значением F1 для задачи классификации, которая будет определять клиентов, склонных к оттоку.
Jupyter тетрадка с решением Kaggle соревнования Leopard Classification Challenge
Increasing your Reddit karma. Help Reddit Moderators improve karma by autosubmitting posts to the correct subreddit. Reddiquette: Cross-post if it belongs to either or both subs?
R | Classification Project
Предсказание сердечно-сосудистых заболеваний.
The telecom operator Interconnect would like to forecast churn of their clients. To ensure loyalty, those who are predicted to leave will be offered promotional codes and special plans.