A deep learning model capable of predicting your income based on Age, Sex, Race, Education, Marital-Status, working hours/week, native country, and occupation with an accuracy of almost 85%.

CS7CS4- Machine Learning- Income Prediction- Kaggle Competition

Individual Machine Learning competition code as part of the 2019/20 Machine Learning module at Trinity College Dublin

Finding Donors for CharityML using supervised learners.

This repo stores the script, the data, and its description for the kernels published on kaggle.

Project that focuses on find the determinants of income using the dataset: https://www.kaggle.com/datasets/fedesoriano/gender-pay-gap-dataset

Udacity Machine Learning Engineer Nanodegree Program Capstone Project

Income Prediction Model deployed as Flask app

In this project, I have predicted Income between two categories based on an individual's demographic and employment details using Logistic regression.

A comprehensive tool for tracking personal finances, including income, spending, investments, and crypto management.

Data science project for feature engineering and classification using as case study the Census Income dataset

Exploratory Data Analysis and Classification Modelling of the Adult Income Dataset aka the Census Income Dataset

TCD ML Comp. 2019/20 - Income Prediction (Ind.)

This project aims to predict the income bracket of individuals based on a variety of features, and presents a holistic comparative analysis between multiple machine learning algorithms through hyperparameter optimization on a binary classification problem.

TCD Machine Learning Kaggle Individual Competition in which one predicted the income of people with Machine Learning using pandas, numpy and sklearn.

To predict whether the income of the individual is above or below 50 K

This project focuses on predicting the income of individuals based on a diverse set of demographic and socio-economic features. Using the Adult Income dataset, I used a Random Forest model to address this classification task.

Building an Income Prediction System Using Machine Learning Model and Deploying it as a Web App

I analyze and explore US Census Bureau Data using Data Visualization techniques to identify salient features useful for predicting an individual's income level. We use those relevant features and multiple classification methods (Decision-Tree, SVM, and K-Nearest Neighbor) to predict the income level for unknown individuals. Our client is a local…