Prediction model for loan default assessment
-
Updated
May 12, 2021 - Jupyter Notebook
Prediction model for loan default assessment
In this project, I will be analyzing 6 seasons to figure out how to succeed in Shark Tank. To find what describes a successful idea, I will be using different statistical tools to show the main characteristics of the best projects. Moreover, I will use machine learning algorithms to predict if your idea will be successful or not.
Diabetes mellitus, commonly known as diabetes is a metabolic disease that causes high blood sugar. The hormone insulin moves sugar from the blood into your cells to be stored or used for energy. With diabetes, your body either doesn’t make enough insulin or can’t effectively use its insulin.
I created a Machine Learning model that can be used to predict customer churn in credit card services.
Отчет по финальному проекту "Отток пользователей" специализации "Машинное обучение и анализ данных"
Classification of retreatment for reinfection and virological failure among people treated with direct acting antiviral therapy for hepatitis C in national pharmacuetical dispensing administrative data
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.
The goal is to find out the employees those who stay and those who leave the company in the upcoming year. Through the various process of selecting, manipulating, transforming data and build the ensemble models, we get a best accuracy for the employee turnover rate.
The Water Quality Checker uses machine learning to analyze water quality parameters such as pH, solids, and conductivity, to determine if water is safe to drink. By inputting the values into the form, the model can predict if the water is fit for consumption or not.
Modelos de classificação de risco de crédito usando algoritmos de Métodos Ensemble
Employee attrition prediction is the use of machine learning algorithms to predict whether an employee will leave their current company. The model uses historical data to learn the patterns and relationships between features and the likelihood of employee attrition
Neural Network and Gradient Boosting Classifier on Predicting Startup Success
Health-insurance-cross-sell-prediction
learning python day 14
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.
HR application to predict if an employee is about to quit
A research study on How do factors like alcohol consumption, age, ethnic background, and medical history affect the risk of developing Alzheimer's disease?
Sports betting is the activity of predicting sports results and placing a wager on the outcome.
Add a description, image, and links to the gradientboostingclassifier topic page so that developers can more easily learn about it.
To associate your repository with the gradientboostingclassifier topic, visit your repo's landing page and select "manage topics."