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Project Category: Machine Learning

CareerMap

CareerMap : Segmenting Job Seekers Using Unsupervised Learning

Project Overview This project applies clustering algorithms to segment job seekers based on their skills, experience, education level, and career goals. The objective is to group individuals into categories that can help recruiters offer better-targeted opportunities and support services. Objective To…

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Predicting House Prices with Regression Models

PriceWise : Predicting House Prices with Regression Models

Project Overview In this project, students built a machine learning model to predict house prices based on features such as square footage, number of bedrooms, location, and more. This real estate-focused problem teaches how regression models can be applied to continuous…

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Salary Estimation Using Regression Models

PayPredict : Salary Estimation Using Regression Models

Project Overview This project focuses on predicting a person’s salary based on features like years of experience, education level, job role, and location. It uses supervised regression techniques to build models that estimate salary ranges for professionals in different industries. Objective…

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Diabetes Risk Detection with Machine Learning

GlucoPredict: Diabetes Risk Detection with Machine Learning

Project Overview This project focuses on building a machine learning model to classify individuals as diabetic or non-diabetic based on health indicators like glucose level, BMI, and age. It uses labeled medical data and applies classification algorithms to assist in early…

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CreditGuard

CreditGuard : Loan Default Prediction Using Supervised Learning

Project Overview In this project, students built a classification model to predict whether a loan applicant is likely to default. Using historical financial data, they applied supervised learning techniques to assess credit risk and support better lending decisions. Objective To develop…

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MindScope

MindScope: Mental Health Risk Classification Using Supervised Learning

Project Overview This project focuses on predicting whether a person is at risk of mental health issues based on personal and workplace factors. Using labeled survey data, students built classification models to understand patterns and make predictions. Objective To use supervised…

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