Salary Prediction: Data Analytics Project
- 1. Salary Prediction Spinnaker Analytics | Balraj Kahare
- 2. Introduction • Salary prediction is a vital aspect of modern workforce management, bridging the gap between employer expectations and employee compensation. • In today's dynamic job market, where talent acquisition and retention are paramount, accurate salary prediction plays a pivotal role in organizational success. • This presentation delves into the intricacies of salary prediction, highlighting its importance, methodologies, and real-world applications.
- 3. Significance of Salary Prediction • Strategic Workforce Planning: Enables organizations to budget effectively for human resources, aligning compensation with strategic goals and market competitiveness. • Talent Acquisition and Retention: Facilitates informed decision-making during recruitment, ensuring competitive offers to attract top talent and retain valuable employees. • Employee Satisfaction: Contributes to job satisfaction by establishing fair and transparent compensation practices, fostering trust and loyalty among employees. • Pay Equity and Diversity: Helps address disparities in pay based on gender, ethnicity, or other demographics, promoting fairness and inclusivity in the workplace.
- 4. Research Objectives • Explore the fundamentals of salary prediction, including key factors influencing compensation levels. • Discuss methodologies for data collection, preprocessing, and model development in salary prediction. • Highlight real-world applications and benefits of accurate salary prediction in various industries. • Provide insights into best practices and challenges in implementing salary prediction systems. Let's embark on a journey to unlock the power of data-driven salary prediction and its transformative impact on organizational success.
- 5. Dataset Dataset Name : ‘Salary_Data.csv’ This simple dataset contains information of the employees regarding their years of experience and salary. Dataset Fields :- ‘YearsExperience’ ‘Salary’
- 6. Libraries These are the following libraries that we’ve imported :- Pandas for Dataframe operations. Numpy for Numeric operations. Matplotlib and Seaborn for Data Visualisation. Sklearn to implement ML Models and Statistical Modelling.
- 7. Importing and Viewing the Dataset
- 10. Visualization We show a regression line in this graph.
- 11. Checking Null Values and Defining X & Y Data
- 12. Simple Linear Regression • First we imported train_test_split from scikit learn for data segregation. • Then we split the data for training and testing after which we created new axis for x column followed by importing the linear regression model and fitting the data into the model. Further we proceeded to predict the salary for the test values.
- 13. Prediction Test We did the actual prediction test after predicting the salary for the test values. We did a salary prediction test for an employee with an assumed years of experience of 3.6 years.
- 14. Analyzing the Prediction We can observe the actual vs. predicted value difference in the graph below.
- 15. Plotting the Error We can see the error plotted in the graph alongside.
- 16. Extracting the Formula for Correct Salary Prediction After printing the Intercept of the model and Coefficient of the line we can observe it forming a line which gives us the above formula.
- 17. Conclusion Unlocking the Power of Salary Prediction Throughout this presentation, we've delved into the realm of salary prediction and its profound impact on organizational success. From understanding the intricacies of compensation factors to exploring methodologies for accurate prediction, we've uncovered the transformative potential of data-driven insights. Key Insights Data-Driven Decision-Making: Embracing data-driven approaches empowers organizations to make informed decisions regarding salary offerings, talent acquisition, and strategic workforce planning. Fairness and Equity: By promoting fairness and equity in compensation practices, salary prediction not only enhances employee satisfaction but also fosters a culture of inclusivity and diversity. Strategic Alignment: Aligning salary strategies with organizational goals ensures that compensation practices support long-term growth, talent retention, and market competitiveness. Looking Ahead As we continue to navigate the evolving landscape of the modern workforce, the role of salary prediction will only become more critical. By staying abreast of emerging trends, leveraging advanced analytics, and fostering a data-driven culture, organizations can unlock the full potential of salary prediction to drive success in the digital age.
- 18. Thank You! We extend our gratitude for your time and engagement throughout this presentation. Should you have any further questions or inquiries, please don't hesitate to reach out.