Machine learning projects often fail not because of bad algorithms but because of messy workflows. In this post, I share five lessons I’ve learned while improving my ML pipelines.

Customer churn is one of the most common challenges faced by businesses today. Retaining existing customers is often more cost-effective than acquiring new ones, which makes churn prediction a high-impact area for data science. In this post, I’ll walk you through how I approached this problem using logistic regression and explained the results with SHAP values.