Computer Vision Project

Summary

A dedicated image-based portfolio piece, building on Phase 9's classifier project with a more original dataset or problem to show independent execution.

How to Learn This

1Choose an image dataset and problem distinct from your Phase 9 practice project.
2Use transfer learning as your primary approach unless you have a specific reason not to.
3Include a short error analysis: what kinds of images does the model get wrong, and why?

Time Series Forecasting Project

Business Case Study With ML Recommendation

More projects in Build Your Data Science Portfolio

End-to-End ML Project (Problem to Deployment)Kaggle Competition Submission NLP Project (Sentiment / Text Classification)Time Series Forecasting Project Business Case Study With ML Recommendation Portfolio Website / GitHub Showcase

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