Predict Health Insurance Owners' who will be interested in Vehicle Insurance
python random-forest logistic-regression imbalanced-data datavisualization randomoversampler xgbclassifier
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xgbclassifier
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In this project, I have created a Machine Learning model using XGBClassifier to Detect Parkinsons Disease with eXtreme Gradient Boosting (XGBoost).
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Heart Attack Analysis & Prediction model created for DataTalks.Club mlzoomcamp course
python data-science machine-learning kaggle classification classification-algorithm classification-model xgbclassifier
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Predicting transaction fraud using classification problems such as Guardian Boosting as well as user interfaces using Streamlite, Accuracy: 98% AUC-ROC
numpy pandas-dataframe eda imblearn sklearn-library matplotlib-pyplot seaborn-plots plotly-express xgbclassifier adaboostclassifier randomforestclassifier streamlit-webapp pickle-file lgbmclassifier gradientboostingclassifier scipy-stats
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In this Python machine learning project, using the Python libraries scikit-learn, numpy, pandas, and xgboost, I have build a model using an XGBClassifier. We’ll load the data, get the features and labels, scale the features, then split the dataset, build an XGBClassifier, and then calculate the accuracy of our model.
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Data fetched by wafers is to be passed through the machine learning pipeline and it is to be determined whether the wafer at hand is faulty or not apparently obliterating the need and thus cost of hiring manual labour.
pipelines flask-api classification-algorithm svc-model simple-imputer xgbclassifier knn-imputer gradientboostingclassifier deployment-docs randomforrestclassifier
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Predict Health Insurance Owners who will be interested in Vehicle Insurance
python random-forest data-visualization logistic-regression imbalanced-data randomoversampler xgbclassifier
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Weather Prediction With Gradient Boost
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Segmenting customers of an audiobook platform and predicting their future purchase.
machine-learning clustering prediction pca-analysis classification kmeans-clustering svm-classifier random-forest-classifier customer-segmentation customer-relationship-management elbow-plot rfm-analysis xgbclassifier
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Real case of classification with machine learning. Analysis of real data from telemarketing campaigns of a Portuguese bank.
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Bank Marketing Classifcation machine learning using 6 Models each of models given another accuracy
numpy sklearn plotly pandas seaborn logisticregression decisiontreeclassifier standardscaler xgbclassifier gaussiannb randomforestclassifier
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Gain a complete and accurate understanding of the disease you’re dealing with.
tensorflow numpy svm pandas logistic-regression pickle gradient-boosting-classifier keras-tensorflow adam-optimizer kneighborsclassifier tensorflowjs matplotlib-pyplot tensorflow2 standardscaler xgbclassifier gaussiannb adaboostclassifier randomforestclassifier extratreesclassifier mlpclassifier
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ReneWind operates wind farms. Unexpected turbine failures are presenting operational and financial problems. This project uses machine learning to develop a model that accurately predict component failure, which will give the firm more control over maintenance scheduling, costs and power generation.
validation cross-validation pipelines logistic-regression confusion-matrix tuning-parameters hyperparameter-tuning decision-tree-classifier oversampling bagging undersampling random-forest-classifier xgboost-classifier heatmap-visualization xgbclassifier adaboostclassifier featureimportances missingvalues gradientboostingclassifier
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Задача от Яндекс.Практикум и Samokat.tech – реализовать векторный поиск и решить усечённую задачу матчинга
python matching sklearn jupyter-notebook pandas python3 xgboost classification cosine-similarity faiss xgbclassifier
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📘 This repository predicts OLA driver churn using ensemble methods—Bagging (Random Forest) and Boosting (XGBoost)—with KNN imputation and SMOTE. It reveals city-wise churn trends and key performance drivers, powering smarter, data-backed retention strategies for the ride-hailing industry.
random-forest exploratory-data-analysis xgboost decision-tree-classifier xgbclassifier bagging-ensemble smote-oversampler boosting-ensemble knn-imputer
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Метод опорних векторів -Support Vector Machine, SVM. Дерева рішень - RandomForestClassifier, XGBClassifier
python numpy reporting scikit-learn pandas classification svm-model svm-classifier random-forest-classifier xgbclassifier
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Using supervised learning on Lending Club loan data to predict default and / or bad loans
data-science machine-learning aws-lambda pca-analysis hyperparameter-optimization hyperparameter-tuning partial kaggle-dataset supervised-machine-learning gridsearch kaggle-api aws-sagemaker xgboost-classifier xgbclassifier standard-scaler gridsearch-tuning
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Clustering bank loan customers using KMeans clustering and predicting their loan statuses using XGBClassifier. The prediction model is explained with SHAP values.
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