Domain: Sales
Tech Stack: Jupyter, Python, scikit-learn, Statsmodels, Pandas, Matplotlib, Seaborn
Objective: To Predict whether a lead will be successfully converted or not based on their data attributes like Time spent on website, Total visits etc
Key achievements: Built a scaleable model operations by performing-
Data Preparation, Preprocessing & Missing value treatment
Exploratory Data Analysis and visualization
Outliers treatment
Dummy Variable Creation
Test-Train Split
Feature Scaling
Feature Selection Using RFE
Checking VIFs
Plotting the Confusion Matrix, Accuracy, Sensitivity, Specificity
Plotting ROC Curve
Finding optimal value of the cut off
Precision-Recall Trade off
Model Building
LinkedIn/Resume:
GitHub/Dataset:
By: arvin
Title: Using Logistic Regression to predict Lead Conversion | Domain: Sales | Tech Stack: Jupyter, Python
Sourced From: www.youtube.com/watch?v=SMshuioeMCA
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