HR Analytics using Logistic Regression (with full Code)

HR Analytics Projects: Predict Offer Declines from Candidates using Logistic Regression [with full Code and Video Explainers]

Offer Drops are a Talent Acquisition Team’s worst nightmare. When a candidate declines an offer at a late stage, just before joining, it costs the Company Time and Money to start the Hiring Process all over again. It leads to Business Impact and Revenue Loss.

In this Project Module, you will learn how to Predict whether a Candidate will ‘Decline’ the Offer or Not based on Historical Data that your Company has, all using Data Science.

The Project uses the power of Data Science, more specifically, the Logistic Regression Algorithm, which is a very powerful Machine Learning Algorithm. We will perform a number of sophisticated steps like Feature Scaling, Feature Elimination, Opmitm Threshold Calculation, and so on, to arrive at the optimum Model performance. The outcome of the Test Data would be a ‘Prediction’ of which Candidates will ‘Decline’ the Offer they have from your company.

This Data Science: Logistic Regression Project exposes you to the following Concepts:

Use of Logistic Regression Algorithm, Preprocessing Techniques, Model Optimisation Techniques

FAQs HR Analytics Projects

Q. What is data science in HR analytics?

Ans: The Data Scientist is a professional working in the HR department, who can apply statistical theory and methods to collect, interpret, and summarize HR data. Based on these data, they can make predictions and present clear, actionable recommendations on HR-related issues.

Q. What makes a data science project for student successful?

Ans: Understanding the business or activity that your data project is part of is key to ensuring its success and the first phase of any sound data analytics student project. To motivate the different actors necessary to get your project from design to production, your project must be the answer to a clear organizational need