Welcome to my capstone project repository. In this project, I analyzed a dataset and built predictive models to provide valuable insights to the Human Resources (HR) department of a large consulting firm. The primary objective is to predict whether or not an employee will leave the company, helping HR make informed decisions to improve employee retention.
This project includes two key deliverables:
- One-Page Summary: A concise summary intended for external stakeholders, presenting the key findings and insights derived from the analysis.
- Complete Code Notebook: A comprehensive Jupyter notebook containing all the code, analysis, and visualizations used in this project.
I followed the PACE framework to complete this project:
- Plan: I started by planning the approach, defining the problem, and outlining the steps required to achieve the project goals.
- Analyze: I performed exploratory data analysis (EDA) to understand the dataset, identify patterns, and uncover potential issues.
- Construct: I built predictive models using machine learning techniques to predict employee attrition. I chose to focus on a machine learning model for this task.
- Execute: I evaluated the model's performance, visualized the results, and interpreted the findings to provide actionable insights for HR.
I utilized a machine learning model to predict employee attrition. The model was evaluated based on its accuracy, precision, recall, and F1-score. These metrics provided a comprehensive understanding of the model's performance and its ability to make accurate predictions.
To enhance the insights provided, I included several data visualizations in the project. These visualizations highlight key trends and patterns in the data, making it easier to communicate the findings to stakeholders.
Throughout the project, I ensured that all analyses and predictions were conducted ethically. This included maintaining data privacy, avoiding bias in the models, and ensuring that the insights provided were used responsibly to benefit both the employees and the organization.
To troubleshoot and find solutions, I utilized various resources, including online documentation, forums, and tutorials. These resources were instrumental in overcoming challenges and ensuring the accuracy and reliability of the analysis.
This capstone project demonstrates my ability to analyze complex datasets, build predictive models, and provide actionable insights to support HR decision-making. The combination of data analysis, machine learning, and ethical considerations ensures that the insights are both valuable and responsible.
Thank you for taking the time to review my project. If you have any questions or feedback, please feel free to reach out.