/Human-Resources

Primary LanguageJupyter NotebookMIT LicenseMIT

🤸 HUMAN RESOURCES STUDY - REGRESSION TECHNIQUES

🔍 PROBLEM AND PRODUCT

In this project I wanted to predict the possibility of a employee to leave using the regression techniques. This will help the company to make previous actions before the employee resigns and give the opportunity to the HR team to improve the working enviroment to make them stay.

So I want to create a table that contains the probability of each employee to leave with the final product looking like this:

image

📑 PROJECT ORGANIZATION

The project is organized following the subtopics below:

  • 📚 Part 1
    • Data Cleaning:
      We verify if that is any missing data.
    • Descriptive Analysis:
      We give an overview analysis of the data and an superficial analysis about the employees that left and stayed the company.
    • Conclusions:
      In this topic we take some superficial conclusions about an overview analysis that we made.
  • 📚 Part 2
    • Data Pre-processing:
      This part we pre-processing the data to apply on our Machine Learning Models.
    • Machine Learning Models:
      In this part we will use two models and compary witch have the best perfomance: - Logistic Regression: - Random Forest:
    • Apply:
      After we analyse the performance of the models we will apply the selected model to a new sample, generating the table that we wanted in our final product, generating the table below: image