Метод опорних векторів -Support Vector Machine, SVM. Дерева рішень - RandomForestClassifier, XGBClassifier

Develop supervised model which predict the loan defaulter in python using XGBClassifer

Health-insurance-cross-sell-prediction

Using supervised learning on Lending Club loan data to predict default and / or bad loans

Malware Detection is a Kaggle Competition held privately which detects the probability of a machine being infected with malware or not given various features of each machine.

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.

classifying a patient has a heart disease or not

MlFlow Project creating pipelines and using Grid-Search Cross Validation to find optimal parameters for Old School Runescape Machine Learning datasets.

Develop a supervised model which predict whether or not participate in financial market in Python and using multivariate analysis ,determine key factors that lead to participation in financial market

In this problem i have tried to explain how XGB algorithm works in case of classification. I have also stated the accuracy score at the end for our XGBClassifier model. The confusion matrix has also been shown for the same. I have used the Kaggle Dataset - Titanic Survivors csv file.

Detecting Parkinson Using extreme gradient boosting(XGBOOSTING) Algorithm.

This is the first project to be completed in Upskill ISA Intelligent Machines. The project was done after the end of the competition. The XGBClassifier used in this model obtained 0.950844 public scores on Kaggle.

Different classification algorithms to predict the species of Iris flowers

Clustering bank loan customers using KMeans clustering and predicting their loan statuses using XGBClassifier. The prediction model is explained with SHAP values.

Detecting Parkinson's using the XGBClassifier

In this classification project, we will use different features like passenger class, sex, age, fare, etc to predict whether a person will survive in titanic or not.

Spam Email Detection using Machine Learning Classifier Algorithms