https://github.com/codeasarjun/predict-the-salary
https://github.com/codeasarjun/predict-the-salary
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/codeasarjun/predict-the-salary
- Owner: codeasarjun
- Created: 2022-07-18T10:24:10.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2024-02-16T06:53:04.000Z (almost 2 years ago)
- Last Synced: 2025-03-16T04:42:21.851Z (10 months ago)
- Language: Jupyter Notebook
- Size: 16.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Predict-the-Salary
This project aims to predict salaries based on survey data using Python, Streamlit, and Linear Regression. The dataset used for this project is the "survey_2021.csv" obtained from Kaggle.
# 🌟 What is Streamlit?
Streamlit is an open-source Python library that makes it easy to create web applications for machine learning and data science projects. It allows developers to quickly build interactive web apps using simple Python scripts, making it an ideal choice for showcasing data analysis and machine learning models.
# 📊 Understanding Linear Regression
Linear Regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. In this project, Linear Regression is employed to predict salary based on various features such as education level, years of experience, job title, etc.
# 📊 The Dataset
The "survey_2021.csv" dataset from Kaggle contains information collected from a survey conducted in 2021. It includes features such as:
Salary
Education Level
Years of Experience
Job Title
Location
Industry
# 🚀 Running the Application
Clone this Repository: Grab your cape and clone this repository to your local machine.
Install Dependencies: Use pip command to install the required dependencies
Dataset Placement: Place the "survey_2021.csv" dataset in the project directory..
Launch the Streamlit App: Run the Streamlit app by executing streamlit run app.py in your terminal. Access the web application through the provided link.
User need to select the country, education level and total work experience
# Output
