To build a classification methodology to determine whether a person makes over 50K per year.
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Updated
Feb 14, 2022 - Jupyter Notebook
To build a classification methodology to determine whether a person makes over 50K per year.
In 2021, a precise forecast of Iran Post's 2021-2022 income was achieved using ARIMA, with only a 1.5\% error. This approach was subsequently extended to estimate the income and traffic for 2022-2023.
a predictive model to determine the income level for people in US. Imputed and manipulated large and high dimensional data using data.table in R. Performed SMOTE as the dataset is highly imbalanced. Developed naïve Bayes, XGBoost and SVM models for classification
Income Tax Calculator is a comprehensive web application designed to provide net income estimates after federal and state taxes. Built with TypeScript, and NextJs, it offers detailed breakdowns for both hourly and salaried income types.
To predict whether the income of the individual is above or below 50 K
Predict whether income exceeds $50K/yr based on census data.
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%.
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
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.
CS7CS4- Machine Learning- Income Prediction- Kaggle Competition
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…
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.
Building a Classification model to predict whether a person's annual Income is more than $50K or below $50K
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