Salary Prediction(Regression Models)

Overview

Developed machine learning models to predict IT salaries based on various factors using Python.
The project involved data preprocessing, model evaluation, and visualization of results.

Features

• Data Preprocessing: Handled missing values and outliers to clean the dataset.
• Model Evaluation: Evaluated multiple regression models, including Linear Regression, Ridge Regression, Lasso, Decision Tree, Random Forest, Gradient Boosting, and XG Boost.
• Best Performing Model: Achieved the best performance using the Random Forest algorithm.
• Dependencies Used:
  • Numpy
  • Pandas
  • Seaborn
  • Matplotlib
  • Sklearn(scikit-learn)
  • XgBoost
  • PyDotPlus