Salary prediction dataset This repository hosts the code and resources for a Salary Prediction project using Multiple Linear Regression. This table contains salary prediction data with 375 rows and 7 columns, including information on age, gender, education level, job title, years of experience, and salary. β₀ is the intercept (the value of Y when all X values are 0). It offers a valuable resource for studying the relationship between income and various socio-demographic factors. May 30, 2023 · Introduction: In this blog post, we will explore the process of salary prediction using linear regression. By analyzing the provided dataset, the model can make accurate predictions if the salaries of new employees is above 100K or not. - aveskh/Employee-Salary-Prediction Jul 4, 2021 · Using Linear Regression Model Problem Statement Suppose the HR department of a company wants to make a model to predict the salary of a new employee based on the data they have on the company. kaggle. [2] 3) Pornthep Khongchai, Pokpong Songmuang, “Improving Students’ Motivation to Study using Salary Prediction System” - proposed prediction model using Decision tree technique with seven features. Each row represents a different employee, and the columns include information such as age, gender, education level, job title, years of experience, and salary. com/git-dibwar/engineering_graduate_salary_prediction/main/Engineering_graduate_salary. We will take an experimental dataset with 3 features and apply multiple linear regression and multiple polynomial regression for salary prediction and compare the accuracy scores. The data can be downloaded from here: NBA Salary Dataset. Predict The Salary of An Indian Engineering Graduate Sep 6, 2019 · Step 1: Load the Dataset If we look at the dataset, we need to predict the salary for an employee who falls under Level 6. Employee Salary Prediction Dataset [16] from Kaggle comprises 375 rows and 7 columns, containing information about employees, including their qualifications, experiences, job title, and salaries. 6% accuracy, interactive web interface, clean dataset, pre-trained model. It is widely used in scenarios like employee churn analysis, recruitment decisions, and financial planning. The project aims to predict salaries based on multiple features such as years of experience, education level, and other relevant factors. Through 19 detailed visualizations, it reveals how factors like employment type and company ratings affect salaries. The two important datasets used are 'NBA Player Stats. The goal is to uncover trends, analyze key factors influencing salaries, and provide predictions based on those factors. Feb 5, 2022 · The dataset above contains 64461 rows and 61columns. Company Job Degree Salary Prediction Dataset 📊💼 Overview Welcome to the Company Job Degree Salary Prediction project! This dataset provides information about job positions in various companies along with the education level of candidates and whether the salary exceeds $100k. 59584548, 47084. Dataset Used The StackOverflow 2023 survey of developers was used to train the model after extracting additional features and preprocessing all the used features. Since the Polynomial Regression model provides a more accurate fit to the dataset, its prediction of $158,862. Project Objective: Lets assume the above table is what the HR Aboout the dataset The dataset consists of a comprehensive collection of salary and demographic information with additional details on years of experience. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. Mar 5, 2024 · Explore the dynamics of compensation in our latest article, 'Predict Salary on the Basis of Years of Experience. Utilizes advanced machine learning techniques, including pipelines and transformers, for robust and accurate predictions. Salary Prediction Data Simple Linear Regression, used in Machine Learning A - Z Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. It includes data Description This report provide Salary Graduate Prediction using regression algorithms A minimal Streamlit app for predicting employee salary based on HR data using a Random Forest model. It explores using linear regression, random forest, and neural networks on a dataset of over 20,000 salaries in the US. Salary prediction model The salary prediction model that is built by Machine Learning sturcture in kaggle competition we are two-man team and 3rd winner in this competition. Contents: Dataset: FileName: Employee_Dataset. 1 Dataset Collection Employee Salary Prediction Dataset [16] from Kaggle comprises 375 rows and 7 columns, containing information about employees, including their qualifications, experiences, job title, and salaries. In this paper, we This table contains salary prediction data with 375 rows and 7 columns, including information on age, gender, education level, job title, years of experience, and salary. Jun 13, 2024 · Introduction: Our goal is to predict salaries accurately based on experience, job role, and performance using machine learning. This project explores employee salaries across industries using data from Kaggle and machine learning models. Keywords included linear regression, machine learning, neural Jul 29, 2025 · This project aims to provide accurate salary predictions for the Indian job market by leveraging machine learning algorithms. This project conducts an Exploratory Data Analysis on salary data to uncover trends in job roles, industries, and company influences on compensation. Aug 3, 2023 · A small dataset (with about 1000 rows) of the salaries of some hypothetical people for learning, practicing, and testing purposes. Job Role Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. Explore and run machine learning code with Kaggle Notebooks | Using data from multiple data sources In our project, we are developing a salary prediction model using machine learning regression technique. Fortunately, technological advancements like Data Science and Machine Learning (ML) have made salary prediction more realistic. Mar 17, 2025 · Extensive experiments on four real-world datasets demonstrate that our method achieves superior performance than state-of-the-art baselines in salary prediction while providing explainable insights into salary-influencing patterns. The goal is to predict the salary of data related positions based on location, company review and job title. The model is built and trained in Google Colab, leveraging basic regression techniques. - Subhralina/Data-Science-Salary-Prediction Explore and run machine learning code with Kaggle Notebooks | Using data from Salary Prediction Data - Simple linear regression This document presents an in-depth analysis of salary prediction, emphasizing its significance in workforce management, talent acquisition, and employee satisfaction. csv and can be found here. Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side. File descriptions EDA-Job Salary Prediction. It helps employers and employees to make estimations of the expected salary. In this case the model will be using the YearsExperience to predict the Salary. read_csv('https://raw. csv at main · alavi-sam/salary-prediction Dec 13, 2023 · Salary Prediction Classification Overview This project involves the analysis of census data, specifically census data from the 1994 Census database. This repository contains the codebase for an employee salary prediction project. csv file consists the data needed to train and test the model. Jul 16, 2024 · Run the Script: python3 salary_prediction. About This project aims to predict salaries based on various factors, such as age, gender, education level, job title, and years of experience. In addition, we proposed a simple and effective ensemble model combining different deep neural network models. This has employee details like Emp_ID,age,salary,gender,experience_years Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. The application enables users to predict salaries for individual employees by inputting details such as Age, Department, Job Title, and Experience Level or perform batch predictions on uploaded CSV datasets. 👨💼 Use Case: HR analytics, salary estimation, AI demo project 📦 Frameworks: Python, Scikit-learn, XGBoost, Streamlit 🧠 Model: XGBoost (best performing The dataset was cleaned and analyzed, revealing insights like a positive correlation between experience and salary. It can be used to analyze the relationship between these variables and predict salaries based on different factors. Explore the relationship between experience and salary, and leverage regression models for accurate salary predictions. It serves as a smaller, focused dataset for initial model training and evaluation. This project aims to predict the salary of employees based on various features using a decision tree classifier algorithm. About the Dataset: The dataset provides an expansive compilation of salary and demographic information, augmented by details regarding years of professional experience Created minimum and maximum salary columns for the positions and parsed the corresponding values out of the raw data Created average salary column Extracted the state where each position is located. Industry Trends: Identifying the most lucrative industries. The data set used Explore and run machine learning code with Kaggle Notebooks | Using data from Data Science, AI & ML Job Salaries in 2025 Apr 27, 2025 · 3. (AI-generated) Classification on Salary whether less than 50K or greater than 50K Salary Prediction using Decision Tree Regression A specific company has an internal salary policy according to the position and hierarchy of each employee. csv') In out prediction task, we used average salary per company, average salary per location, average salary per job category, and numbers of job advertisements per location published, as input features to linear equation. The demographic attributes include age, gender, education, country, and race, providing a diverse range of variables for Aboout the dataset The dataset consists of a comprehensive collection of salary and demographic information with additional details on years of experience. - abinayagoudjandhyala/employee-salary-prediction This project leverages data analysis and machine learning techniques to predict employee salaries based on various factors, including demographics, job roles, education, and performance metrics. This project provides an in-depth analysis of the AI job market and predicts salary trends using machine learning models. Jul 22, 2025 · This salary prediction model can be used to make informed salary estimates based on individual characteristics, making it a valuable tool for HR analytics and compensation planning. ipynb - Explore job description datasets and also provides a brief modular exploratory data analysis tutorial for the data science project. I then create and test machine learning models to predict employee salary from the data. We have used a dataset containing 6704 rows and 6 columns to develop and evaluate our salary prediction model. Oct 3, 2024 · In this blog post, we will explore how to use Python and machine learning to predict whether an adult earns more than $50,000 per year based on demographic and employment-related features. Therefore, this is a The Data Science Salaries Dataset is an invaluable resource for understanding the evolving salary landscape in the data science industry. Sep 27, 2023 · Python: Predicting Employee Salary with Machine Learning 11 minute read Background The dataset in this project explores factors that influence employee performance and satisfaction. Perfect for learning ML, web development, and practical HR applications Jul 24, 2025 · This dataset contains synthetic employee data with attributes like position, education level, industry, location, and years of experience. Jan 3, 2025 · The dataset was sourced from Kaggle. Our research focuses on data-driven strategies for campus placement and salary prediction in education, empowering students with career insights. Navigate the correlation between years of This project aims to predict the salary of software developers based on survey data obtained from Stack Overflow. This dataset contains information about the salaries of employees at a company. In this Explore and run machine learning code with Kaggle Notebooks | Using data from Salary Prediction Data - Simple linear regression This document presents an in-depth analysis of salary prediction, emphasizing its significance in workforce management, talent acquisition, and employee satisfaction. Oct 9, 2024 · The salary prediction dataset is a composite problem for analyzing the salary. The Salary Prediction App forecasts employee salaries based on years at the company, satisfaction level, and monthly hours worked. - 012aafaw/Salary-Prediction We will be splitting our dataset into training and testing and we will be calculating the weight matrix using linear algebra. - shaadclt/Employee-Salary-Prediction-DecisionTreeClassifier salary prediction using linear regressionSomething went wrong and this page crashed! If the issue persists, it's likely a problem on our side. The model is built using Python's data science libraries and follows the principles of linear regression. Stack Overflow Developer Survey 2023 Dataset [17] is a larger dataset consisting of 48,019 New dataset with 1 replacing the values greater than 1 The next thing to do is to combine the two data frames, filtered_df_2, which holds all the words and their counts, and the sliced_df, which has a few columns and my target column. dec Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. Five different supervised ML algorithms are trained using survey data from the Saudi Arabian labor market to estimate mean annual salary across economic Estimate Monthly Salaries Using Experience, Education, and Work Hours Mar 15, 2023 · The dataset chosen is Salary Dataset — Simple linear regression from Kaggle. The project addresses challenges in accurately predicting salaries due to variability across industries and job roles, utilizing a synthetic dataset for analysis and predictive Mar 23, 2023 · I’m grateful to the Danish Data Science Association for providing this rich dataset. Flexible Data Ingestion. It uses the XGBoost model trained on the UCI Adult Income dataset and deployed via Streamlit. Predictive models are developed based on occupational features and organizational characteristics. About Salary Prediction based on Experience: A machine learning project that predicts salaries using a dataset of employees' experience. INTRODUCTION Nowadays as we will see, data mining is becoming latest trend within the computer sector which involves finding beneficial patterns and knowledge from systems. Jul 22, 2025 · Employee Salary Prediction Overview This capstone project develops a Streamlit web application for predicting employee salaries using a Gradient Boosting Regressor model. Discover data preprocessing, analysis, model selection, and training for insights into compensation management. Salary Prediction Project (Python) The purpose of this project is to use data transformation and machine learning to create a model that will predict a salary when given years of experience, job type, college degree, college major, industry, and miles from a metropolis. at https://www. Dec 15, 2021 · import matplotlib. Our project comprises of 2 parts. Objectives This analysis aims to observe the Salary Dataset. This dataset was created to help teach linear regression. Sep 12, 2022 · A holistic occupational and economy-wide framework for salary prediction is developed and tested using statistical machine learning (ML). - GitHub - shaecodes/Employee-Salary-Prediction: This project predicts employee salaries based on characteristics like experience, age, gender, department, location, and travel requirements. It is Position_Salaries. The dataset contains over 90,000 surveys with 84 features, which include informatio In this paper, we focus on studying the job prediction using different deep neural network models including TextCNN, Bi-GRU-LSTM-CNN, and Bi-GRU-CNN with various pre-trained word embeddings on the IT job dataset. Oct 20, 2024 · How well does years of experience predict salary? My goal here is to create a simple linear regression model between the years of experience and salary from the “Salary Dataset - Simple linear regression” dataset from the user Allena Venkata Sai Abhishe on Kaggle. 363 seconds. Job Salary Prediction. 84301944, 84743. 59116071, 108279. com/static/assets/app. array([ 64972. Abstract— This project aims to develop a Salary Prediction Web Application for software developers worldwide. It outlines research objectives, methodologies for data collection, and real-world applications using a dataset of employee experiences and salaries, leveraging various analytical libraries. 68292158, 56499. githubusercontent. csv' and 'NBA Salaries. I investigate how different variables influence employee salary. This model is expressed as: Y = β₀ + β₁X₁ + β₂X₂ + β₃X₃ + + βₙXₙ + ε Y is the dependent variable. 2% while linear regression had the fastest training time of 0. The dataset is sourced from Kaggle and contains comprehensive data on AI-related job roles, requirements, and salary information. 95. Salary Prediction Introduction This project aims to predict salaries based on various factors, such as age, gender, education level, job title, and years of experience. 45 suggests that the requested salary of $160,000 is reasonable and aligns with market expectations for a Regional Manager with 2 years of experience. It visualizes salary trends, ranks industries, and compares prediction models based on RMSE and R-squared scores. 11361727, 87567. Keywords included linear regression, machine learning, neural This salary prediction model leverages machine learning techniques, including Random Forest, Decision Tree, and Linear Regression, to estimate salaries based on individual attributes such as age, gender, education level, job title, and years of experience. csv" dataset to forecast salaries. , YearsExperience and Salary, and 30 observations. In this study, we investigate whether and how machine learning, particularly regression trees and random-forest regression, can achieve high-quality salary predictions on a large dataset of salary data. 48066074, 54616. The goal is to classify the salary of the employee on the basis of year of 🚀 Complete ML Project: Salary Prediction using Linear Regression & Streamlit. Mar 28, 2025 · Conclusion In this article, we have built a machine learning model to predict employee salaries using linear regression. Additionally, it provides tools for data visualization and model evaluation. The following graph shows the Salary vs Experience (Training Set). It uses a cleaned dataset and applies machine learning models like Linear Regression, Support Vector Regression, and Random Forest Regressor, with hyperparameter tuning done via GridSearchCV for improved accuracy. The method which proves to be efficient will be selected to proceed with Sep 23, 2022 · Therefore, most studies focus on very specific industries or markets or use quite outdated or small datasets. In conclusion, our salary prediction model, trained on a well-preprocessed dataset, successfully predicts salaries based on various factors. 5 — So we really do not need the first column “Position”. It has 3 columns - "Position", "Level" and "Salary" and describes the approximate salary range for an employee based on what level he falls under. We will implement the mathematical code from scratch and utilize essential tools like Predict the salary according to the featuresSomething went wrong and this page crashed! If the issue persists, it's likely a problem on our side. Job titles can be categorized based on the words they contain such as "director", Jul 19, 2025 · The Employee Salary Prediction project aims to build a machine learning model that accurately estimates the salary (or monthly income) of employees based on various personal, performance, and organizational attributes. Created a state column Title column was created to show the different categories for the posted roles such as data engineer, deep learning, analyst, Explore our GitHub repo for a comprehensive employee salary prediction project. The . ipynb - Implement the machine learning algorithm, establish the baseline model, select the best model to predict the salary on the test data. With comprehensive details on salaries across various roles, experience levels, and geographic locations, this dataset empowers data professionals, researchers, and hiring managers to analyze trends and benchmark compensation effectively. The corner stone of this study is a dataset provided by ADZUNA. Setup Explore and run machine learning code with Kaggle Notebooks | Using data from Salary Prediction dataset The code essentially preprocesses salary data, encodes categorical features, trains a Decision Tree Regression model, and makes predictions based on the model. A person’s salary will have more or less related to the profession and the person’s Feb 23, 2023 · In this blog post, we’ll take a deep dive into the world of salary prediction, exploring the use of Linear Regression and Tree Regression Models on a dataset containing information on age This ML-powered web app allows users to input various employee attributes and predicts whether the salary is more than ₹50K or not. β₁, β₂, β₃, , βₙ are the coefficients (slopes) for each independent variable X₁, X₂, X₃, , Xₙ. csv'. com This file contains detailed information about data professionals, including their salaries, designations, departments, and more. Mar 1, 2025 · Abstract: In today’s world, salary is the primary source of motivation for many regular employees, which makes salary prediction very important for both employers and employees. The primary goal is to provide organizations with data-driven insights to optimize compensation dataset=pd. js?v=948bceb7ee7fbb4e4743:2:1564255. - tulika105/Predict-employee-salary Jul 26, 2023 · The dataset contains two columns namely: “YearsExperience” and “Salary”. The Random Forest model outperforms the others, achieving the highest R-squared score. Let’s start cleaning!!! Selecting and keeping the columns/features needed for the prediction: When building a machine learning model in real Employee_Salary_Prediction ML Workflow using Google Colab & Streamlit This repository contains two Google Colab notebooks that demonstrate a complete machine learning workflow—from data preprocessing to deploying a Streamlit web application for predicting employee salaries. Salary Prediction with Machine Learning For salary prediction, we need to find relationships in the data on how the salary is determined. The dataset consists of 3 columns, Sl. Initially, we compile a comprehensive dataset from multiple organizational databases, incorporating relevant Machine Learning courses with 100+ Real-time projects Start Now!! Program 1 Salary Prediction Dataset # Salary Prediction Based on Skills and Experience using Gradient Boosting import pandas as pd from sklearn. The neural network model achieved the highest accuracy at 83. ' Delve into the world of predictive modeling, unlocking insights into how professional experience shapes earning potential. No. The application leverages machine learning to provide an approximate estimate of salaries based on various developer attributes, such as location, experience, and skills. In today’s world, salary is the primary source of motivation for many regular employees, which makes salary prediction very important for both employers and employees. The dataset consists of fifteen predictor … The hiring manager can use these predictions to negotiate the salary with the potential employee. The weight matrix will be calculated based on the training data set. This repository contains the implementation of an employee salary prediction model using machine learning techniques in Python. pyplot as plt import pandas as pd dataset = pd. 96288896, 63089. The target variable is Avg Salary, which is predicted across various input attributes such as, Num companies, Industry, Sector, Revenues, Competitiors, Employer Provided, Hourly Salary, Min Salary, Max Salary, Company Name, job state, same state, age, python yn,R yn A simple machine learning model that predicts salaries based on the number of years of experience using a dataset from Kaggle. py Conclusion Predicting employee salaries based on years of experience using linear regression is a straightforward yet powerful application of machine Machine learning model that will predict a salary given years of experience This project uses the concepts of Multiple Linear Regression and Label Encoding to predict salary on the basis of age, gender, years of experience, education level and job title. This document outlines a project aimed at constructing a robust salary prediction system using machine learning techniques, focusing on various factors like education, experience, and location to forecast salaries. And it shows that the model predicts well to make future decisions for HR department to make the salary predictions based on the experience of the applicants. model_selection import train_test_split from Explore and run machine learning code with Kaggle Notebooks | Using data from Salary Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. In this blog post, we will explore how to use Python and machine learning to predict whether an adult earns more than $50,000 per year based on demographic and A comprehensive analysis and predictive modeling of the "Salary Data. The demographic attributes include age, gender, education, country, and race, providing a diverse range of variables for Oct 31, 2022 · In this article, I will take you through the task of salary prediction with Machine Learning using Python. The Employee Productivity and Satisfaction HR Data was Jul 14, 2025 · EMPLOYEE SALARY PREDICTION EDUNET 📁 This repository contains all project work from my 6-week AICTE–Edunet Foundation internship on AI & ML, powered by IBM SkillsBuild. It is suitable for training and testing machine learning models for salary prediction tasks in HR and analytics projects. Gain actionable knowledge for informed career decisions, negotiation strategies, and employer decision-making. Users should supplement these predictions with current market research and professional advice for a comprehensive understanding of prevailing salary expectations. For example if an employee is a Manager - he falls in Level 4 and should get around $80,000. With a larger dataset and more complete features, this model can help This document discusses using machine learning models for salary prediction. Dataset Overview: The dataset used for this project was sourced from Kaggle and includes various features that can influence salary predictions: Name: First and Last Name Gender: Male or Female Date of Joining (DOJ): When the individual joined the company Current Date Project Overview The focus of the Demographic-Based Salary Prediction project is to develop a predictive model that estimates the salaries of individuals from diverse countries and races based on their demographic attributes. Jul 29, 2025 · This project aims to provide accurate salary predictions for the Indian job market by leveraging machine learning algorithms. . In today's exercise, we want to fit this data into a linear model. The project includes a Power BI dashboard that provides interactive visualizations to analyze and present insights derived from the prediction results. It's a basic example of using machine learning for salary prediction. csv This is the dataset used for training ML Models Notebook 1: Employee Salary Prediction based on Country and Race Aboout the dataset The dataset consists of a comprehensive collection of salary and demographic information with additional details on years of experience. read_csv (r'C:\Users\saikr\OneDrive\Desktop\Data science by prakash sir\Machine Learning\15th. Explore and run machine learning code with Kaggle Notebooks | Using data from Salary Prediction dataset Nov 23, 2023 · An example prediction was demonstrated, encoding a new data point for a Senior Data Scientist job in California and predicting the salary using the trained decision tree regressor. The analysis focuses on: Salary Distribution: Understanding how salaries are spread across different roles. For this task, we need to have a dataset based on salaries. Dataset- First lets look at the dataset. The job is to train a model to predict salaries of Data Scientists, lets get modelling! The dataset contains structured salary information across various job roles, employment types, industries, and locations. 49003029, 111103. - Subhralina/Data-Science-Salary-Prediction Furthermore, economic trends and industry fluctuations since the dataset's end date may further affect the accuracy of salary predictions. Index Terms - Salary prediction, salary, raise, salary increment, job, professional growth. Using ML, we predict salaries based on experience, education, and job roles. X₁, X₂, X₃ Sep 12, 2022 · A holistic occupational and economy-wide framework for salary prediction is developed and tested using statistical machine learning (ML). js?v=948bceb7ee7fbb4e4743:2:1561969. I. Employment Status Impact: How full-time, part-time, and contract jobs affect salary levels. 50408462, 115811. Oct 3, 2024 · Predicting whether an individual’s salary exceeds a certain threshold is a common classification problem in data science. Using machine learning techniques, it aims to forecast the salaries of employees based on various features such as age, gender, years of experience, education level and job title. model is well capable to predict precise value. Five different supervised ML algorithms are trained using survey data from the Saudi Arabian labor market to estimate mean annual salary across economic In this paper, we focus on studying the job prediction using different deep neural network models including TextCNN, Bi-GRU-LSTM-CNN, and Bi-GRU-CNN with various pre-trained word embeddings on the IT job dataset. The data can be used for salary prediction, trend analysis, and HR analytics. Aug 30, 2024 · Our comprehensive strategy continuously improves machine learning algorithms for more accurate school placement predictions, despite drawbacks such as a short dataset and reliance on statistical data. Tech job positions and salaries from glassdoor. - salary-prediction/Salary Data. The conclusion highlights the Comprehensive Employee Dataset: Analyze Performance, Salaries, and Trends Easily Sep 3, 2019 · Step 2: Fit Linear Regression model to dataset First we will build a simple Linear Regression model to see what prediction it makes and then compare it to the prediction made by the Polynomial A regression model that predicts the salary of any Data Science job opening based on location, skills and experience. The system takes into account multiple factors that influence salary determination in India, making it a valuable tool for job seekers, HR professionals, and career counselors. dhigrd naiw rybnz gxru znhjw mawxcda oqef yomdd rsz trzm kjdofg ytmr hgo ceug zsxp