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.

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.

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.

I created a Machine Learning model that can be used to predict customer churn in credit card services.

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.

learning python day 14

Prediction model for loan default assessment

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.

Отчет по финальному проекту "Отток пользователей" специализации "Машинное обучение и анализ данных"

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

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.

Health-insurance-cross-sell-prediction

Modelos de classificação de risco de crédito usando algoritmos de Métodos Ensemble

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

HR application to predict if an employee is about to quit