Classify Retail Product Photos for an E-Commerce Marketplace
Overview
What this challenge is about.
Fine-tune a CNN on 10,000 product photos for 12-category classification, compare to a title baseline, and deliver a model and memo for a verifiable certificate.
The scenario
The marketplace (around 80 staff, around 200k active sellers) loses around 4 percent of new listings because sellers abandon when miscategorized listings get few views; better category suggestion is the most-requested seller-quality feature.
The Brief
What you'll do, and what you'll demonstrate.
Train an image classifier that beats the title-only baseline on top-3 category accuracy by at least 10 points.
Earning criteria — what you'll demonstrate
- Fine-tune a pretrained CNN on a small classification task
- Apply standard image augmentation for robustness
- Evaluate classification with top-1 and top-3 accuracy + confusion matrix
- Communicate results to a non-technical product audience
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Image Classification
Apply image classification to solve real industry problems and demonstrate production-level capability.
- Transfer Learning
Apply transfer learning to solve real industry problems and demonstrate production-level capability.
- Pytorch
Apply pytorch to solve real industry problems and demonstrate production-level capability.
- Model Evaluation
Apply model evaluation to solve real industry problems and demonstrate production-level capability.
- Data Augmentation
Apply data augmentation to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Computer Vision Engineer
Fine-tuning a CNN classifier with proper splits and a non-technical writeup is the entry-level CV engineering task every product team assigns to a new hire.
This challenge sharpens
- image-classification
- transfer-learning
- model-evaluation
Machine Learning Engineer
Train/val/test discipline and clean evaluation are habits MLEs carry into every project; this challenge builds them on a small, tractable problem.
This challenge sharpens
- pytorch
- model-evaluation
- data-augmentation
AI Engineer
Translating model results into a memo a PM can act on is the AI-engineer skill that gets work shipped.
This challenge sharpens
- image-classification
- model-evaluation
- transfer-learning