AI Skill Showcase

Submissions are closed! Thank you for applying to SEE-DR!

Welcome! 👋

This repository is designed as a lightweight take-home assessment to help us get to know your skills with AI/ML, Python, and Git workflows.
It should take 1–2 hours and is meant to be fun and flexible.

---

📌 Purpose

• Demonstrate basic familiarity with Python + Jupyter/Colab.
• Showcase ability to train or apply a simple model.
• Practice working with Git branches, commits, and merge requests.
• Give you room to add your own creativity.

---

Steps

1. Fork or clone this repository.
2. Create a new branch named feature/<your-name>.
3. Add a Google Colab named <your_name>_showcase.ipynb that includes:
   • Step 1: Generate or load two images (from data, synthetic, or AI model).
   • Step 2: Apply a transformation or train a simple model that produces different results.
   • Step 3: Display both original and transformed/predicted outcomes side-by-side.
4. Commit and push your branch with just one ipynb file (edit requirements if needed, making sure it's up to date with master for easy merging).
5. Open a Merge Request (PR) into main, document and explain your code in the description, then request review.
6. Be prepared to explain in the interview along with any technical skills if we ask!

---

Rubric

• Notebook runs end-to-end without errors.
• Code is clear, commented, and reproducible.
• Explanation in the PR is not written by GPT, but with your own words. Doesn't have to be crazy.
• Different from previous submissions. No p71s out here
• Shows two distinct images/outcomes.
• Follows Git workflow (branch, commit, MR).
• You can use AI to bounce off ideas and get clarity, but we expect you to understand what you're writing
• Shows your commitment and your technical skills (it is a team project after all)

---

🚀 Example

We’ve provided example.ipynb as a Google Colab-friendly demo.
It trains a simple classifier and shows two separate predictions to illustrate the workflow. Check out everyone's notebooks! Great ideas so far:

• Creating heatmaps sourced from images online (Advitiya's)
• William's Pokemon card classifier
• Malaria classification by Andrew Yang

---

🔧 Setup

Install dependencies:

pip install -r requirements.txt