This project aims to build a predictive model for estimating salaries based on an individual's years of professional experience. Leveraging a dataset containing salary information coupled with corresponding years of experience, the project employs a linear regression approach to develop and assess the model's accuracy.

• pandas: A powerful data manipulation tool for handling the dataset.
• numpy: Essential for performing numerical computations efficiently.
• matplotlib: Used to visualize the data distribution and model performance.
• scikit-learn (sklearn): Provides convenient tools for model training, testing, and evaluation.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression

1. Data Preprocessing: The dataset is loaded from a CSV file, and any incomplete or missing entries are addressed by removing corresponding rows.

2. Feature Extraction: The key features, namely 'Years of Experience' and 'Salary', are extracted from the dataset.

3. Train-Test Split: The dataset is partitioned into training and testing subsets, with 90% of the data reserved for training and the remaining 10% for testing.

4. Model Training: A Linear Regression model is trained using the training data, aiming to establish a relationship between years of experience and salary.

5. Model Testing and Prediction: The trained model is applied to predict salaries based on years of experience. The predicted salaries are then compared against the actual salary data.

6. Performance Evaluation: The effectiveness of the model is assessed by evaluating the consistency between predicted salaries and actual salaries within the test set.

7. Visualization: Visual representations, such as scatter plots and line plots, are employed to illustrate the model's predictive performance and validate its accuracy.

To clone the repository and access the project files, use the following command:

git clone https://github.com/Arjun-Regmi-Chhetri/salary-prediction-machine-learning

cd salary-prediction-machine-learning