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Lead Scoring Dataset

Overview

This dataset contains lead scoring data for X Education, a company that provides online courses. The dataset is designed for binary classification to predict whether a lead will convert to a customer using an LLM.

Features

The processed dataset includes the following 7 key features:

  1. Prospect ID - Unique identifier for each lead
  2. Lead Origin - How the lead was generated (API, Landing Page Submission, etc.)
  3. Lead Source - Specific source of the lead (Google, Direct Traffic, Organic Search, etc.)
  4. Last Activity - Most recent interaction (Email Opened, Page Visited, etc.)
  5. Tags - Lead categorization tags (Ringing, Will revert after reading email, etc.)
  6. What is your current occupation - Lead's current job status (Student, Unemployed, etc.)
  7. Converted - Target variable indicating conversion (0/1)

Usage

The processed dataset is available on Hugging Face Hub at: shawhin/lead-scoring-x

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("shawhin/lead-scoring-x")

# Access train, validation, and test splits
train_data = dataset['train']
valid_data = dataset['valid'] 
test_data = dataset['test']

License

Please refer to the original Kaggle dataset license for usage terms.

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