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Name: Neeraj Dheeman

Type: User

Bio: I am a data scientist with a passion for turning data into insights that drive business value. I have a strong technical background in statistics and computer.

Location: Prayagraj, Uttar pradesh, India

Neeraj Dheeman's Projects

-determining-status-for-loan-applicants icon -determining-status-for-loan-applicants

This ML project is an automated system designed to assess the eligibility of loan applicants based on their financial status and credit history. The system uses machine learning algorithms to analyze a variety of data sources, including credit reports, employment history, income levels, and other financial data.

employee-promotion-prediction- icon employee-promotion-prediction-

An employee promotion prediction project aims to develop a model that can predict the likelihood of an employee being promoted within an organization. This project typically involves analyzing a variety of data points related to employee performance, such as job tenure, education level, past job performance, and skills.

employee-turnover-prediction icon employee-turnover-prediction

The employee turnover rate prediction ML model is a statistical tool that uses machine learning algorithms to forecast the likelihood of an employee leaving a company within a specific timeframe. This model is designed to analyze various factors that contribute to employee attrition, including job satisfaction, compensation, work-life balance, and

optimizing-agricultural-production icon optimizing-agricultural-production

The Optimizing Agricultural Production Machine Learning project is a cutting-edge solution aimed at enhancing crop yield and productivity by leveraging data-driven insights. Through the use of advanced machine learning algorithms, this project helps farmers make informed decisions on various aspects of agriculture.

weight-category-prediction icon weight-category-prediction

A weight category prediction ML model is a type of machine learning algorithm that is designed to predict the weight category of an individual based on a set of input features. These features may include age, gender, height, body measurements, and other relevant parameters.

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