Design an ML pipeline for demand forecasting
Last updated: October 26, 2025
Quick Overview
Design an end-to-end ML system for demand forecasting, covering data, features, model selection, training, and serving.
Walmart
Machine Learning
Data Scientist
Walmart
October 26, 2025Data Scientist
Technical Screen
Machine Learning
Medium
398
13
3,946 solved
Design an end-to-end ML system for demand forecasting, covering data, features, model selection, training, and serving.
How to Approach This
- Understand the bias-variance trade-off. High training accuracy but low test accuracy signals overfitting.
- Choose evaluation metrics carefully based on the problem. Accuracy alone is often insufficient.
- Feature engineering is often more impactful than model selection.
- Know when to use tree-based models (tabular data) vs neural networks (unstructured data).
- Handle class imbalance with SMOTE, class weights, or appropriate loss functions.
Sharpen Your Skills on Codemia
Practice similar problems with our interactive workspace, get AI feedback, and track your progress.
Explore ML Interview PrepSubmit Your Answer
Markdown supported