booleanhunter / lucrative-learners

A machine learning project aimed at enhancing the lead conversion rate for X Education (as part of program requirements for IIITB)

Lucrative Learners

This case study aims at enhancing the lead conversion rate for X Education, an online education company that sells professional courses to industry experts. The project focuses on identifying the most promising leads, also known as "Hot Leads," to increase the efficiency of the company's sales and marketing efforts.

To achieve this goal, the project will:

1. Develop a logistic regression model that assigns a lead score between 0 and 100 to each lead. A higher score indicates a hot lead with a high likelihood of converting, while a lower score signifies a cold lead with a low probability of conversion.
2. Ensure that the model can adapt to new requirements or changes in the company's lead evaluation strategy as specified in a separate document.
3. Provide recommendations for implementation.

Instructions to run

You can use Google Colaboratory to run the project.

Alternatively, you can run it in your Linux machine by running the following on your terminal:

1. Install python3.7 or above and pip3
2. Create a python virtual environment using venv python -m venv ~/python-virtual-environments/lucrative-learners
3. Activate virtual environment: source ~/python-virtual-environments/lucrative-learners/bin/activate
4. Install JupyterLab: pip install jupyter-lab
5. Install required libraries and other dependencies: pip install -r requirements.text
6. Launch JupyterLab: jupyter-lab